This notebook contains the code samples found in Chapter 3, Section 5 of Deep Learning with R. Note that the original text features far more content, in particular further explanations and figures: in this notebook, you will only find source code and related comments.


Data Exploration & Preparation

Attribute Name Explanation Remarks
ID Client number
CODE_GENDER Gender
FLAG_OWN_CAR Is there a car
FLAG_OWN_REALTY Is there a property
CNT_CHILDREN Number of children
AMT_INCOME_TOTAL Annual income
NAME_INCOME_TYPE Income category
NAME_EDUCATION_TYPE Education level
NAME_FAMILY_STATUS Marital status
NAME_HOUSING_TYPE Way of living
DAYS_BIRTH Birthday Count backwards from current day (0), -1 means yesterday
DAYS_EMPLOYED Start date of employment Count backwards from current day(0). If positive, it means the person unemployed.
FLAG_MOBIL Is there a mobile phone
FLAG_WORK_PHONE Is there a work phone
FLAG_PHONE Is there a phone
FLAG_EMAIL Is there an email
OCCUPATION_TYPE Occupation
CNT_FAM_MEMBERS Family size

Main task


Some hints


Important notes


Data import

# install.packages("tidymodels")
# install.packages("themis")
library(here)
library(tidyverse)
library(ggplot2)
library(dplyr)
library(tensorflow)
library(tfdatasets)
library(tidymodels)
library(keras)
library(caret)
library(themis)
#LOAD DATA
setwd(getwd())
dataIn = "../Data/Dataset-part-2.csv"
data_in <- read.csv(dataIn,header = TRUE, sep =',')
#View(data_in)
data <- data.frame(data_in)
summary(data)
       ID          CODE_GENDER        FLAG_OWN_CAR       FLAG_OWN_REALTY     CNT_CHILDREN    
 Min.   :5008804   Length:67614       Length:67614       Length:67614       Min.   : 0.0000  
 1st Qu.:5465941   Class :character   Class :character   Class :character   1st Qu.: 0.0000  
 Median :5954270   Mode  :character   Mode  :character   Mode  :character   Median : 0.0000  
 Mean   :5908133                                                            Mean   : 0.4206  
 3rd Qu.:6289080                                                            3rd Qu.: 1.0000  
 Max.   :7965248                                                            Max.   :19.0000  
 AMT_INCOME_TOTAL  NAME_INCOME_TYPE   NAME_EDUCATION_TYPE NAME_FAMILY_STATUS NAME_HOUSING_TYPE 
 Min.   :  26100   Length:67614       Length:67614        Length:67614       Length:67614      
 1st Qu.: 112500   Class :character   Class :character    Class :character   Class :character  
 Median : 157500   Mode  :character   Mode  :character    Mode  :character   Mode  :character  
 Mean   : 178867                                                                               
 3rd Qu.: 225000                                                                               
 Max.   :6750000                                                                               
   DAYS_BIRTH     DAYS_EMPLOYED      FLAG_MOBIL FLAG_WORK_PHONE    FLAG_PHONE       FLAG_EMAIL    
 Min.   :-25201   Min.   :-17531   Min.   :1    Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:-19438   1st Qu.: -2886   1st Qu.:1    1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :-15592   Median : -1305   Median :1    Median :0.0000   Median :0.0000   Median :0.0000  
 Mean   :-15914   Mean   : 62022   Mean   :1    Mean   :0.2028   Mean   :0.2742   Mean   :0.1005  
 3rd Qu.:-12347   3rd Qu.:  -321   3rd Qu.:1    3rd Qu.:0.0000   3rd Qu.:1.0000   3rd Qu.:0.0000  
 Max.   : -7489   Max.   :365243   Max.   :1    Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
 OCCUPATION_TYPE    CNT_FAM_MEMBERS     status         
 Length:67614       Min.   : 1.000   Length:67614      
 Class :character   1st Qu.: 2.000   Class :character  
 Mode  :character   Median : 2.000   Mode  :character  
                    Mean   : 2.174                     
                    3rd Qu.: 3.000                     
                    Max.   :20.000                     
plot(data$status)

##Cleanup

# Check for duplicates 
sum(duplicated(data))
[1] 0
# No duplicates

#Remove ID (irrelevant) and FLAG_MOBIL (always 1)
data <- data %>% select(-ID, -FLAG_MOBIL)
cols <- c("CODE_GENDER","FLAG_OWN_CAR","FLAG_OWN_REALTY","NAME_INCOME_TYPE","NAME_EDUCATION_TYPE", "NAME_FAMILY_STATUS", "NAME_HOUSING_TYPE","FLAG_WORK_PHONE","FLAG_PHONE","FLAG_EMAIL", "OCCUPATION_TYPE","status")
cols
 [1] "CODE_GENDER"         "FLAG_OWN_CAR"        "FLAG_OWN_REALTY"     "NAME_INCOME_TYPE"   
 [5] "NAME_EDUCATION_TYPE" "NAME_FAMILY_STATUS"  "NAME_HOUSING_TYPE"   "FLAG_WORK_PHONE"    
 [9] "FLAG_PHONE"          "FLAG_EMAIL"          "OCCUPATION_TYPE"     "status"             
data[cols] <- lapply(data[cols],factor)

# Replacing empty values with "Unknown"
levels(data$OCCUPATION_TYPE) <- c(levels(data$OCCUPATION_TYPE), "Unknown")
data$OCCUPATION_TYPE[is.na(data$OCCUPATION_TYPE)] <- "Unknown"

# Replacing C and X in Status
levels(data$status)[levels(data$status)=="C"] <- "6"
#data$status[data$status == "X"] <- 7
levels(data$status)[levels(data$status)=="X"] <- "7"
# #Convert factors into numericals
# data %<>% mutate_if(is.factor, as.numeric)

summary(data)
 CODE_GENDER FLAG_OWN_CAR FLAG_OWN_REALTY  CNT_CHILDREN     AMT_INCOME_TOTAL              NAME_INCOME_TYPE
 F:43924     N:43107      N:21090         Min.   : 0.0000   Min.   :  26100   Commercial associate:15640  
 M:23690     Y:24507      Y:46524         1st Qu.: 0.0000   1st Qu.: 112500   Pensioner           :11982  
                                          Median : 0.0000   Median : 157500   State servant       : 5044  
                                          Mean   : 0.4206   Mean   : 178867   Student             :    4  
                                          3rd Qu.: 1.0000   3rd Qu.: 225000   Working             :34944  
                                          Max.   :19.0000   Max.   :6750000                               
                                                                                                          
                    NAME_EDUCATION_TYPE            NAME_FAMILY_STATUS           NAME_HOUSING_TYPE
 Academic degree              :   38    Civil marriage      : 6016    Co-op apartment    :  227  
 Higher education             :16890    Married             :44906    House / apartment  :60307  
 Incomplete higher            : 2306    Separated           : 4125    Municipal apartment: 2303  
 Lower secondary              :  716    Single / not married: 9528    Office apartment   :  587  
 Secondary / secondary special:47664    Widow               : 3039    Rented apartment   : 1020  
                                                                      With parents       : 3170  
                                                                                                 
   DAYS_BIRTH     DAYS_EMPLOYED    FLAG_WORK_PHONE FLAG_PHONE FLAG_EMAIL    OCCUPATION_TYPE  CNT_FAM_MEMBERS 
 Min.   :-25201   Min.   :-17531   0:53904         0:49071    0:60819    Unknown    :20699   Min.   : 1.000  
 1st Qu.:-19438   1st Qu.: -2886   1:13710         1:18543    1: 6795    Laborers   :12425   1st Qu.: 2.000  
 Median :-15592   Median : -1305                                         Sales staff: 6899   Median : 2.000  
 Mean   :-15914   Mean   : 62022                                         Core staff : 6059   Mean   : 2.174  
 3rd Qu.:-12347   3rd Qu.:  -321                                         Managers   : 4950   3rd Qu.: 3.000  
 Max.   : -7489   Max.   :365243                                         Drivers    : 4427   Max.   :20.000  
                                                                         (Other)    :12155                   
     status     
 0      :52133  
 1      : 6491  
 7      : 5790  
 6      : 1805  
 2      :  712  
 5      :  374  
 (Other):  309  

Preprocessing

set.seed(1)
trainIndex <- initial_split(data, prop = 0.8, strata = status) 
trainingSet <- training(trainIndex)
testSet <- testing(trainIndex)
status_folds <- vfold_cv(trainingSet, v = 10, strata = status)
status_folds
#  10-fold cross-validation using stratification 
# Remove outliers (Out of 1.5x Interquartile Range) only on training set
# CNT_CHILDREN
boxplot(trainingSet$CNT_CHILDREN, horizontal=TRUE, main="CNT_CHILDREN")

Q1_Child <- quantile(trainingSet$CNT_CHILDREN, .25)
Q3_Child <- quantile(trainingSet$CNT_CHILDREN, .75)
IQR_Child <- IQR(trainingSet$CNT_CHILDREN)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$CNT_CHILDREN > (Q1_Child - 1.5*IQR_Child) & trainingSet$CNT_CHILDREN < (Q3_Child + 1.5*IQR_Child))
dim(trainingSet)
[1] 53330    17
# AMT_INCOME_TOTAL
boxplot(trainingSet$AMT_INCOME_TOTAL, horizontal=TRUE, main="AMT_INCOME_TOTAL")

Q1_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .25)
Q3_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .75)
IQR_AIT <- IQR(trainingSet$AMT_INCOME_TOTAL)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$AMT_INCOME_TOTAL > (Q1_AIT - 1.5*IQR_AIT) & trainingSet$AMT_INCOME_TOTAL < (Q3_AIT + 1.5*IQR_AIT))
dim(trainingSet)
[1] 51748    17
set.seed(5)
preprocRecipe <-
  recipe(status ~., data = data) %>%
  step_dummy(all_nominal(), -status,  one_hot = TRUE) %>%
  step_range(all_predictors(), -all_nominal(), min = 0, max = 1)%>%
  step_smote(status, over_ratio = 1) %>%
 # step_downsample(status, under_ratio = 1, skip=TRUE) %>%
 # step_smote(status, over_ratio = 1, skip=TRUE) %>%
 # step_smotenc(status, over_ratio = 1) %>%
 # step_adasyn(status, over_ratio = 1) %>%
 # step_nearmiss(status, over_ratio = 1) %>%
   
  step_dummy(status,  one_hot = TRUE)# %>%

In this step the above defined receipt is extracted using the prep() function, and then use the bake() function to transform a set of data based on that recipe.

# retain = TRUE and new_data = NULL ensures that pre-processed trainingSet is returned 
trainingSet_processed <- preprocRecipe %>%
  prep(trainingSet, retain = TRUE) %>%
  bake(new_data = NULL)
testSet_processed <- preprocRecipe %>%
  prep(testSet) %>%
  bake(new_data =testSet)

#summary(trainingSet_processed)

Check data


# sum(trainingSet_processed$status_X0 == 1)
# sum(trainingSet_processed$status_X1 == 1)
# sum(trainingSet_processed$status_X2 == 1)
# sum(trainingSet_processed$status_X3 == 1)
# sum(trainingSet_processed$status_X4 == 1)
# sum(trainingSet_processed$status_X5 == 1)
# sum(trainingSet_processed$status_X6 == 1)
# sum(trainingSet_processed$status_X7 == 1)

# Turn data frame into data matrix
matrix_data <- trainingSet_processed %>% select(-tail(names(trainingSet_processed), 8))
matrix_targets <- trainingSet_processed %>% select(tail(names(trainingSet_processed), 8))

matrix_data_test  <- testSet_processed %>% select(-tail(names(testSet_processed), 8))
matrix_targets_test  <- testSet_processed %>% select(tail(names(testSet_processed), 8))

# summarize the class distribution
percentage <- 100-prop.table(table(data$status)) * 100

#class_counts <- table(data$status)
class_counts <- matrix_targets %>%
  summarize_all(funs(sum(. == 1)))
majority_class_count <- max(class_counts)
relative_class_counts <-  majority_class_count /class_counts

cbind(freq=table(data$status), percentage=percentage)
   freq percentage
0 52133   22.89615
1  6491   90.39992
2   712   98.94696
3   195   99.71160
4   114   99.83140
5   374   99.44686
6  1805   97.33043
7  5790   91.43668
#Subset only 100 entries for testing
#matrix_data <- matrix_data[1:100, ]
#matrix_targets <- matrix_targets[1:100, ]

Build Model

#train_data <- matrix_data
train_data <- data.matrix(matrix_data)
test_data <- data.matrix(matrix_data_test)
train_targets <- data.matrix(matrix_targets)
test_targets <- data.matrix(matrix_targets_test)



# Function to build the model
build_model <- function() {
  model <- keras_model_sequential() %>%
    #layer_batch_normalization(axis = -1L, input_shape = dim(train_data)[[2]]) %>%
    layer_dense(units = 128, activation = "relu", input_shape = dim(train_data)[[2]]) %>%
    #layer_dense(units = 1024, activation = "relu") %>%
    layer_dense(units = 1024, activation = "relu") %>%
    layer_dense(units = 1024, activation = "relu") %>%
    layer_dense(units = 128, activation = "relu") %>%
    #layer_dropout(0.3) %>%
    layer_dense(units = 8, activation = "softmax") 

  model %>% compile(
    optimizer = optimizer_sgd(learning_rate = 0.02),
    #optimizer = optimizer_adam(),
    loss = "categorical_crossentropy",
    metrics = "categorical_accuracy"
  )

}
#Yannick
#install.packages("kerasR")
# library(kerasR)
# model <- keras_model_sequential()
# model %>%
#          layer_dense(units = 64, activation = 'relu', dim(train_data)[[2]]) %>%
#          layer_dropout(rate = 0.2) %>%
#          # layer_dense(units = 30, activation = 'relu') %>%
#          # layer_dropout(rate = 0.3) %>%
#          layer_dense(units = 20, activation = 'relu') %>%
#          layer_dropout(rate = 0.2) %>%
#          layer_dense(units = 8, activation = 'softmax')
# summary(model)
# model %>%
#          compile(loss = 'categorical_crossentropy',
#                  optimizer = 'adam',
#                  metrics = 'accuracy')
# history <- model %>%
#          fit(train_data,
#              train_targets,
#              epochs = 1500,
#              batch_size = 1024,
#              validation_split = 0.2,
#              verbose =2,
#              class_weight = list(relative_class_counts))
# plot(history)
# model %>%
#          evaluate(test_data, test_targets)
# pred <- model %>% predict(test_data, batch_size = 32)
# y_pred = round(pred)
# # Confusion matrix
# library(caret)
# confusion_matrix <- caret::confusionMatrix(matrix(pred), matrix(test_targets))
# length(test_targets)
# table(Predicted = round(pred), Actual = test_targets)

K-Fold-Validation


k <- 2
indices <- sample(1:nrow(train_data))
folds <- cut(indices, breaks = k, labels = FALSE)

num_epochs <- 1500
all_acc_histories <- NULL
for (i in 1:k) {
  cat("processing fold #", i, "\n")

  val_indices <- which(folds == i, arr.ind = TRUE)
  val_data <- train_data[val_indices,] #test_data#
  val_targets <- train_targets[val_indices,] #test_targets#

  partial_train_data <- train_data[-val_indices,]
  partial_train_targets <- train_targets[-val_indices,]
  model <- build_model()

  # Train the model (in silent mode, verbose=0)
  # Batch size https://stats.stackexchange.com/questions/153531/what-is-batch-size-in-neural-network
  # One epoch = one forward pass and one backward pass of all the training examples
  # Batch size = the number of training examples in one forward/backward pass. The higher the batch size, the more memory space you'll need.
  # Number of iterations = number of passes, each pass using [batch size] number of examples. To be clear, one pass = one forward pass + one backward pass (we do not count the forward pass and backward pass as two different passes).
  # Batch size 32 much faster than 1, also the smaller the batch the less accurate the estimate of the gradient will be.
  history <- model %>% fit(
    partial_train_data, partial_train_targets,
    validation_data = list(val_data, val_targets),
    epochs = num_epochs, batch_size = 8192, verbose = 2#, class_weights = percentage
  )
  acc_history <- history$metrics$val_categorical_accuracy
  all_acc_histories <- rbind(all_acc_histories, acc_history)
}
processing fold # 1 
Epoch 1/1500
20/20 - 2s - loss: 2.0792 - categorical_accuracy: 0.1386 - val_loss: 2.0731 - val_categorical_accuracy: 0.1426 - 2s/epoch - 79ms/step
Epoch 2/1500
20/20 - 0s - loss: 2.0688 - categorical_accuracy: 0.1610 - val_loss: 2.0636 - val_categorical_accuracy: 0.2028 - 489ms/epoch - 24ms/step
Epoch 3/1500
20/20 - 1s - loss: 2.0598 - categorical_accuracy: 0.2204 - val_loss: 2.0549 - val_categorical_accuracy: 0.2598 - 510ms/epoch - 26ms/step
Epoch 4/1500
20/20 - 0s - loss: 2.0512 - categorical_accuracy: 0.2787 - val_loss: 2.0463 - val_categorical_accuracy: 0.2964 - 463ms/epoch - 23ms/step
Epoch 5/1500
20/20 - 0s - loss: 2.0425 - categorical_accuracy: 0.3064 - val_loss: 2.0374 - val_categorical_accuracy: 0.3251 - 481ms/epoch - 24ms/step
Epoch 6/1500
20/20 - 0s - loss: 2.0336 - categorical_accuracy: 0.3331 - val_loss: 2.0284 - val_categorical_accuracy: 0.3411 - 480ms/epoch - 24ms/step
Epoch 7/1500
20/20 - 0s - loss: 2.0244 - categorical_accuracy: 0.3426 - val_loss: 2.0191 - val_categorical_accuracy: 0.3492 - 486ms/epoch - 24ms/step
Epoch 8/1500
20/20 - 0s - loss: 2.0149 - categorical_accuracy: 0.3471 - val_loss: 2.0094 - val_categorical_accuracy: 0.3482 - 473ms/epoch - 24ms/step
Epoch 9/1500
20/20 - 1s - loss: 2.0050 - categorical_accuracy: 0.3496 - val_loss: 1.9990 - val_categorical_accuracy: 0.3512 - 500ms/epoch - 25ms/step
Epoch 10/1500
20/20 - 0s - loss: 1.9944 - categorical_accuracy: 0.3505 - val_loss: 1.9879 - val_categorical_accuracy: 0.3513 - 460ms/epoch - 23ms/step
Epoch 11/1500
20/20 - 0s - loss: 1.9828 - categorical_accuracy: 0.3489 - val_loss: 1.9760 - val_categorical_accuracy: 0.3486 - 461ms/epoch - 23ms/step
Epoch 12/1500
20/20 - 0s - loss: 1.9705 - categorical_accuracy: 0.3463 - val_loss: 1.9631 - val_categorical_accuracy: 0.3471 - 453ms/epoch - 23ms/step
Epoch 13/1500
20/20 - 0s - loss: 1.9573 - categorical_accuracy: 0.3451 - val_loss: 1.9495 - val_categorical_accuracy: 0.3453 - 474ms/epoch - 24ms/step
Epoch 14/1500
20/20 - 0s - loss: 1.9433 - categorical_accuracy: 0.3440 - val_loss: 1.9350 - val_categorical_accuracy: 0.3441 - 472ms/epoch - 24ms/step
Epoch 15/1500
20/20 - 0s - loss: 1.9284 - categorical_accuracy: 0.3426 - val_loss: 1.9195 - val_categorical_accuracy: 0.3448 - 457ms/epoch - 23ms/step
Epoch 16/1500
20/20 - 0s - loss: 1.9125 - categorical_accuracy: 0.3433 - val_loss: 1.9032 - val_categorical_accuracy: 0.3453 - 491ms/epoch - 25ms/step
Epoch 17/1500
20/20 - 0s - loss: 1.8958 - categorical_accuracy: 0.3431 - val_loss: 1.8861 - val_categorical_accuracy: 0.3417 - 456ms/epoch - 23ms/step
Epoch 18/1500
20/20 - 0s - loss: 1.8784 - categorical_accuracy: 0.3417 - val_loss: 1.8683 - val_categorical_accuracy: 0.3416 - 468ms/epoch - 23ms/step
Epoch 19/1500
20/20 - 0s - loss: 1.8605 - categorical_accuracy: 0.3426 - val_loss: 1.8502 - val_categorical_accuracy: 0.3434 - 460ms/epoch - 23ms/step
Epoch 20/1500
20/20 - 0s - loss: 1.8422 - categorical_accuracy: 0.3442 - val_loss: 1.8318 - val_categorical_accuracy: 0.3440 - 473ms/epoch - 24ms/step
Epoch 21/1500
20/20 - 0s - loss: 1.8237 - categorical_accuracy: 0.3458 - val_loss: 1.8132 - val_categorical_accuracy: 0.3470 - 461ms/epoch - 23ms/step
Epoch 22/1500
20/20 - 0s - loss: 1.8049 - categorical_accuracy: 0.3490 - val_loss: 1.7944 - val_categorical_accuracy: 0.3516 - 486ms/epoch - 24ms/step
Epoch 23/1500
20/20 - 0s - loss: 1.7860 - categorical_accuracy: 0.3526 - val_loss: 1.7755 - val_categorical_accuracy: 0.3550 - 470ms/epoch - 24ms/step
Epoch 24/1500
20/20 - 0s - loss: 1.7671 - categorical_accuracy: 0.3565 - val_loss: 1.7567 - val_categorical_accuracy: 0.3630 - 464ms/epoch - 23ms/step
Epoch 25/1500
20/20 - 0s - loss: 1.7484 - categorical_accuracy: 0.3661 - val_loss: 1.7381 - val_categorical_accuracy: 0.3701 - 460ms/epoch - 23ms/step
Epoch 26/1500
20/20 - 0s - loss: 1.7297 - categorical_accuracy: 0.3730 - val_loss: 1.7196 - val_categorical_accuracy: 0.3755 - 476ms/epoch - 24ms/step
Epoch 27/1500
20/20 - 0s - loss: 1.7112 - categorical_accuracy: 0.3809 - val_loss: 1.7011 - val_categorical_accuracy: 0.3849 - 460ms/epoch - 23ms/step
Epoch 28/1500
20/20 - 0s - loss: 1.6929 - categorical_accuracy: 0.3888 - val_loss: 1.6829 - val_categorical_accuracy: 0.3963 - 467ms/epoch - 23ms/step
Epoch 29/1500
20/20 - 0s - loss: 1.6747 - categorical_accuracy: 0.3968 - val_loss: 1.6649 - val_categorical_accuracy: 0.4014 - 473ms/epoch - 24ms/step
Epoch 30/1500
20/20 - 0s - loss: 1.6568 - categorical_accuracy: 0.4032 - val_loss: 1.6475 - val_categorical_accuracy: 0.4088 - 475ms/epoch - 24ms/step
Epoch 31/1500
20/20 - 0s - loss: 1.6393 - categorical_accuracy: 0.4109 - val_loss: 1.6300 - val_categorical_accuracy: 0.4109 - 458ms/epoch - 23ms/step
Epoch 32/1500
20/20 - 0s - loss: 1.6221 - categorical_accuracy: 0.4155 - val_loss: 1.6132 - val_categorical_accuracy: 0.4193 - 459ms/epoch - 23ms/step
Epoch 33/1500
20/20 - 0s - loss: 1.6055 - categorical_accuracy: 0.4201 - val_loss: 1.5969 - val_categorical_accuracy: 0.4229 - 468ms/epoch - 23ms/step
Epoch 34/1500
20/20 - 0s - loss: 1.5894 - categorical_accuracy: 0.4242 - val_loss: 1.5813 - val_categorical_accuracy: 0.4292 - 456ms/epoch - 23ms/step
Epoch 35/1500
20/20 - 0s - loss: 1.5740 - categorical_accuracy: 0.4283 - val_loss: 1.5661 - val_categorical_accuracy: 0.4328 - 474ms/epoch - 24ms/step
Epoch 36/1500
20/20 - 0s - loss: 1.5591 - categorical_accuracy: 0.4321 - val_loss: 1.5515 - val_categorical_accuracy: 0.4331 - 477ms/epoch - 24ms/step
Epoch 37/1500
20/20 - 0s - loss: 1.5447 - categorical_accuracy: 0.4354 - val_loss: 1.5374 - val_categorical_accuracy: 0.4381 - 490ms/epoch - 24ms/step
Epoch 38/1500
20/20 - 0s - loss: 1.5308 - categorical_accuracy: 0.4382 - val_loss: 1.5241 - val_categorical_accuracy: 0.4425 - 473ms/epoch - 24ms/step
Epoch 39/1500
20/20 - 0s - loss: 1.5174 - categorical_accuracy: 0.4419 - val_loss: 1.5109 - val_categorical_accuracy: 0.4432 - 481ms/epoch - 24ms/step
Epoch 40/1500
20/20 - 0s - loss: 1.5044 - categorical_accuracy: 0.4447 - val_loss: 1.4979 - val_categorical_accuracy: 0.4484 - 474ms/epoch - 24ms/step
Epoch 41/1500
20/20 - 0s - loss: 1.4917 - categorical_accuracy: 0.4502 - val_loss: 1.4855 - val_categorical_accuracy: 0.4540 - 494ms/epoch - 25ms/step
Epoch 42/1500
20/20 - 0s - loss: 1.4794 - categorical_accuracy: 0.4568 - val_loss: 1.4734 - val_categorical_accuracy: 0.4613 - 469ms/epoch - 23ms/step
Epoch 43/1500
20/20 - 0s - loss: 1.4675 - categorical_accuracy: 0.4627 - val_loss: 1.4618 - val_categorical_accuracy: 0.4675 - 490ms/epoch - 25ms/step
Epoch 44/1500
20/20 - 1s - loss: 1.4559 - categorical_accuracy: 0.4668 - val_loss: 1.4505 - val_categorical_accuracy: 0.4720 - 504ms/epoch - 25ms/step
Epoch 45/1500
20/20 - 1s - loss: 1.4448 - categorical_accuracy: 0.4709 - val_loss: 1.4397 - val_categorical_accuracy: 0.4745 - 537ms/epoch - 27ms/step
Epoch 46/1500
20/20 - 0s - loss: 1.4340 - categorical_accuracy: 0.4749 - val_loss: 1.4291 - val_categorical_accuracy: 0.4753 - 458ms/epoch - 23ms/step
Epoch 47/1500
20/20 - 0s - loss: 1.4236 - categorical_accuracy: 0.4771 - val_loss: 1.4188 - val_categorical_accuracy: 0.4805 - 486ms/epoch - 24ms/step
Epoch 48/1500
20/20 - 0s - loss: 1.4134 - categorical_accuracy: 0.4807 - val_loss: 1.4092 - val_categorical_accuracy: 0.4812 - 469ms/epoch - 23ms/step
Epoch 49/1500
20/20 - 0s - loss: 1.4037 - categorical_accuracy: 0.4841 - val_loss: 1.3993 - val_categorical_accuracy: 0.4853 - 483ms/epoch - 24ms/step
Epoch 50/1500
20/20 - 0s - loss: 1.3941 - categorical_accuracy: 0.4867 - val_loss: 1.3900 - val_categorical_accuracy: 0.4908 - 460ms/epoch - 23ms/step
Epoch 51/1500
20/20 - 0s - loss: 1.3849 - categorical_accuracy: 0.4901 - val_loss: 1.3808 - val_categorical_accuracy: 0.4929 - 479ms/epoch - 24ms/step
Epoch 52/1500
20/20 - 0s - loss: 1.3760 - categorical_accuracy: 0.4932 - val_loss: 1.3721 - val_categorical_accuracy: 0.4955 - 481ms/epoch - 24ms/step
Epoch 53/1500
20/20 - 1s - loss: 1.3672 - categorical_accuracy: 0.4958 - val_loss: 1.3638 - val_categorical_accuracy: 0.4996 - 522ms/epoch - 26ms/step
Epoch 54/1500
20/20 - 0s - loss: 1.3588 - categorical_accuracy: 0.4993 - val_loss: 1.3550 - val_categorical_accuracy: 0.5013 - 460ms/epoch - 23ms/step
Epoch 55/1500
20/20 - 0s - loss: 1.3504 - categorical_accuracy: 0.5026 - val_loss: 1.3469 - val_categorical_accuracy: 0.5059 - 459ms/epoch - 23ms/step
Epoch 56/1500
20/20 - 0s - loss: 1.3423 - categorical_accuracy: 0.5066 - val_loss: 1.3391 - val_categorical_accuracy: 0.5104 - 480ms/epoch - 24ms/step
Epoch 57/1500
20/20 - 0s - loss: 1.3345 - categorical_accuracy: 0.5103 - val_loss: 1.3315 - val_categorical_accuracy: 0.5099 - 479ms/epoch - 24ms/step
Epoch 58/1500
20/20 - 0s - loss: 1.3267 - categorical_accuracy: 0.5142 - val_loss: 1.3236 - val_categorical_accuracy: 0.5170 - 490ms/epoch - 24ms/step
Epoch 59/1500
20/20 - 0s - loss: 1.3191 - categorical_accuracy: 0.5182 - val_loss: 1.3165 - val_categorical_accuracy: 0.5193 - 486ms/epoch - 24ms/step
Epoch 60/1500
20/20 - 1s - loss: 1.3117 - categorical_accuracy: 0.5224 - val_loss: 1.3088 - val_categorical_accuracy: 0.5239 - 538ms/epoch - 27ms/step
Epoch 61/1500
20/20 - 0s - loss: 1.3043 - categorical_accuracy: 0.5252 - val_loss: 1.3019 - val_categorical_accuracy: 0.5270 - 489ms/epoch - 24ms/step
Epoch 62/1500
20/20 - 1s - loss: 1.2971 - categorical_accuracy: 0.5282 - val_loss: 1.2943 - val_categorical_accuracy: 0.5284 - 504ms/epoch - 25ms/step
Epoch 63/1500
20/20 - 0s - loss: 1.2902 - categorical_accuracy: 0.5308 - val_loss: 1.2893 - val_categorical_accuracy: 0.5339 - 484ms/epoch - 24ms/step
Epoch 64/1500
20/20 - 0s - loss: 1.2832 - categorical_accuracy: 0.5337 - val_loss: 1.2805 - val_categorical_accuracy: 0.5356 - 491ms/epoch - 25ms/step
Epoch 65/1500
20/20 - 1s - loss: 1.2763 - categorical_accuracy: 0.5363 - val_loss: 1.2736 - val_categorical_accuracy: 0.5359 - 501ms/epoch - 25ms/step
Epoch 66/1500
20/20 - 1s - loss: 1.2697 - categorical_accuracy: 0.5383 - val_loss: 1.2672 - val_categorical_accuracy: 0.5394 - 506ms/epoch - 25ms/step
Epoch 67/1500
20/20 - 0s - loss: 1.2631 - categorical_accuracy: 0.5415 - val_loss: 1.2607 - val_categorical_accuracy: 0.5431 - 474ms/epoch - 24ms/step
Epoch 68/1500
20/20 - 0s - loss: 1.2565 - categorical_accuracy: 0.5440 - val_loss: 1.2541 - val_categorical_accuracy: 0.5431 - 474ms/epoch - 24ms/step
Epoch 69/1500
20/20 - 0s - loss: 1.2501 - categorical_accuracy: 0.5464 - val_loss: 1.2482 - val_categorical_accuracy: 0.5477 - 489ms/epoch - 24ms/step
Epoch 70/1500
20/20 - 0s - loss: 1.2441 - categorical_accuracy: 0.5489 - val_loss: 1.2414 - val_categorical_accuracy: 0.5497 - 497ms/epoch - 25ms/step
Epoch 71/1500
20/20 - 0s - loss: 1.2376 - categorical_accuracy: 0.5510 - val_loss: 1.2353 - val_categorical_accuracy: 0.5492 - 474ms/epoch - 24ms/step
Epoch 72/1500
20/20 - 0s - loss: 1.2319 - categorical_accuracy: 0.5521 - val_loss: 1.2293 - val_categorical_accuracy: 0.5560 - 467ms/epoch - 23ms/step
Epoch 73/1500
20/20 - 1s - loss: 1.2253 - categorical_accuracy: 0.5551 - val_loss: 1.2230 - val_categorical_accuracy: 0.5562 - 512ms/epoch - 26ms/step
Epoch 74/1500
20/20 - 1s - loss: 1.2193 - categorical_accuracy: 0.5567 - val_loss: 1.2170 - val_categorical_accuracy: 0.5565 - 505ms/epoch - 25ms/step
Epoch 75/1500
20/20 - 0s - loss: 1.2130 - categorical_accuracy: 0.5588 - val_loss: 1.2118 - val_categorical_accuracy: 0.5592 - 470ms/epoch - 24ms/step
Epoch 76/1500
20/20 - 0s - loss: 1.2076 - categorical_accuracy: 0.5603 - val_loss: 1.2049 - val_categorical_accuracy: 0.5622 - 477ms/epoch - 24ms/step
Epoch 77/1500
20/20 - 0s - loss: 1.2014 - categorical_accuracy: 0.5624 - val_loss: 1.1990 - val_categorical_accuracy: 0.5633 - 459ms/epoch - 23ms/step
Epoch 78/1500
20/20 - 0s - loss: 1.1957 - categorical_accuracy: 0.5637 - val_loss: 1.1934 - val_categorical_accuracy: 0.5647 - 477ms/epoch - 24ms/step
Epoch 79/1500
20/20 - 1s - loss: 1.1909 - categorical_accuracy: 0.5652 - val_loss: 1.1879 - val_categorical_accuracy: 0.5667 - 508ms/epoch - 25ms/step
Epoch 80/1500
20/20 - 0s - loss: 1.1846 - categorical_accuracy: 0.5671 - val_loss: 1.1845 - val_categorical_accuracy: 0.5680 - 469ms/epoch - 23ms/step
Epoch 81/1500
20/20 - 0s - loss: 1.1791 - categorical_accuracy: 0.5695 - val_loss: 1.1802 - val_categorical_accuracy: 0.5696 - 458ms/epoch - 23ms/step
Epoch 82/1500
20/20 - 0s - loss: 1.1735 - categorical_accuracy: 0.5707 - val_loss: 1.1715 - val_categorical_accuracy: 0.5745 - 489ms/epoch - 24ms/step
Epoch 83/1500
20/20 - 0s - loss: 1.1681 - categorical_accuracy: 0.5724 - val_loss: 1.1688 - val_categorical_accuracy: 0.5730 - 483ms/epoch - 24ms/step
Epoch 84/1500
20/20 - 0s - loss: 1.1634 - categorical_accuracy: 0.5738 - val_loss: 1.1609 - val_categorical_accuracy: 0.5765 - 490ms/epoch - 25ms/step
Epoch 85/1500
20/20 - 0s - loss: 1.1578 - categorical_accuracy: 0.5764 - val_loss: 1.1583 - val_categorical_accuracy: 0.5775 - 494ms/epoch - 25ms/step
Epoch 86/1500
20/20 - 1s - loss: 1.1526 - categorical_accuracy: 0.5783 - val_loss: 1.1484 - val_categorical_accuracy: 0.5819 - 519ms/epoch - 26ms/step
Epoch 87/1500
20/20 - 1s - loss: 1.1482 - categorical_accuracy: 0.5803 - val_loss: 1.1507 - val_categorical_accuracy: 0.5755 - 517ms/epoch - 26ms/step
Epoch 88/1500
20/20 - 1s - loss: 1.1440 - categorical_accuracy: 0.5822 - val_loss: 1.1420 - val_categorical_accuracy: 0.5838 - 520ms/epoch - 26ms/step
Epoch 89/1500
20/20 - 0s - loss: 1.1626 - categorical_accuracy: 0.5753 - val_loss: 1.2817 - val_categorical_accuracy: 0.5183 - 498ms/epoch - 25ms/step
Epoch 90/1500
20/20 - 1s - loss: 1.2090 - categorical_accuracy: 0.5581 - val_loss: 1.1305 - val_categorical_accuracy: 0.5920 - 516ms/epoch - 26ms/step
Epoch 91/1500
20/20 - 1s - loss: 1.1265 - categorical_accuracy: 0.5911 - val_loss: 1.1235 - val_categorical_accuracy: 0.5929 - 503ms/epoch - 25ms/step
Epoch 92/1500
20/20 - 1s - loss: 1.1212 - categorical_accuracy: 0.5927 - val_loss: 1.1178 - val_categorical_accuracy: 0.5941 - 521ms/epoch - 26ms/step
Epoch 93/1500
20/20 - 0s - loss: 1.1156 - categorical_accuracy: 0.5953 - val_loss: 1.1154 - val_categorical_accuracy: 0.5932 - 490ms/epoch - 25ms/step
Epoch 94/1500
20/20 - 1s - loss: 1.1123 - categorical_accuracy: 0.5969 - val_loss: 1.1144 - val_categorical_accuracy: 0.5973 - 512ms/epoch - 26ms/step
Epoch 95/1500
20/20 - 1s - loss: 1.1454 - categorical_accuracy: 0.5818 - val_loss: 1.1738 - val_categorical_accuracy: 0.5742 - 501ms/epoch - 25ms/step
Epoch 96/1500
20/20 - 1s - loss: 1.1209 - categorical_accuracy: 0.5945 - val_loss: 1.0983 - val_categorical_accuracy: 0.6026 - 515ms/epoch - 26ms/step
Epoch 97/1500
20/20 - 0s - loss: 1.0957 - categorical_accuracy: 0.6036 - val_loss: 1.0931 - val_categorical_accuracy: 0.6050 - 458ms/epoch - 23ms/step
Epoch 98/1500
20/20 - 1s - loss: 1.0901 - categorical_accuracy: 0.6056 - val_loss: 1.0880 - val_categorical_accuracy: 0.6057 - 733ms/epoch - 37ms/step
Epoch 99/1500
20/20 - 0s - loss: 1.1670 - categorical_accuracy: 0.5739 - val_loss: 1.3034 - val_categorical_accuracy: 0.5134 - 460ms/epoch - 23ms/step
Epoch 100/1500
20/20 - 0s - loss: 1.1246 - categorical_accuracy: 0.5943 - val_loss: 1.0809 - val_categorical_accuracy: 0.6105 - 467ms/epoch - 23ms/step
Epoch 101/1500
20/20 - 0s - loss: 1.0783 - categorical_accuracy: 0.6121 - val_loss: 1.0752 - val_categorical_accuracy: 0.6122 - 476ms/epoch - 24ms/step
Epoch 102/1500
20/20 - 1s - loss: 1.0719 - categorical_accuracy: 0.6139 - val_loss: 1.0696 - val_categorical_accuracy: 0.6146 - 532ms/epoch - 27ms/step
Epoch 103/1500
20/20 - 0s - loss: 1.0707 - categorical_accuracy: 0.6146 - val_loss: 1.0853 - val_categorical_accuracy: 0.6057 - 486ms/epoch - 24ms/step
Epoch 104/1500
20/20 - 0s - loss: 1.0850 - categorical_accuracy: 0.6066 - val_loss: 1.0950 - val_categorical_accuracy: 0.5999 - 477ms/epoch - 24ms/step
Epoch 105/1500
20/20 - 0s - loss: 1.0654 - categorical_accuracy: 0.6177 - val_loss: 1.0571 - val_categorical_accuracy: 0.6198 - 487ms/epoch - 24ms/step
Epoch 106/1500
20/20 - 0s - loss: 1.0528 - categorical_accuracy: 0.6229 - val_loss: 1.0501 - val_categorical_accuracy: 0.6250 - 492ms/epoch - 25ms/step
Epoch 107/1500
20/20 - 0s - loss: 1.0530 - categorical_accuracy: 0.6215 - val_loss: 1.0845 - val_categorical_accuracy: 0.6039 - 494ms/epoch - 25ms/step
Epoch 108/1500
20/20 - 1s - loss: 1.2491 - categorical_accuracy: 0.5495 - val_loss: 1.0519 - val_categorical_accuracy: 0.6253 - 528ms/epoch - 26ms/step
Epoch 109/1500
20/20 - 0s - loss: 1.0450 - categorical_accuracy: 0.6282 - val_loss: 1.0404 - val_categorical_accuracy: 0.6304 - 496ms/epoch - 25ms/step
Epoch 110/1500
20/20 - 0s - loss: 1.0369 - categorical_accuracy: 0.6312 - val_loss: 1.0343 - val_categorical_accuracy: 0.6313 - 488ms/epoch - 24ms/step
Epoch 111/1500
20/20 - 0s - loss: 1.0312 - categorical_accuracy: 0.6329 - val_loss: 1.0282 - val_categorical_accuracy: 0.6346 - 472ms/epoch - 24ms/step
Epoch 112/1500
20/20 - 0s - loss: 1.0261 - categorical_accuracy: 0.6346 - val_loss: 1.0241 - val_categorical_accuracy: 0.6340 - 473ms/epoch - 24ms/step
Epoch 113/1500
20/20 - 0s - loss: 1.0259 - categorical_accuracy: 0.6327 - val_loss: 1.0391 - val_categorical_accuracy: 0.6255 - 474ms/epoch - 24ms/step
Epoch 114/1500
20/20 - 0s - loss: 1.0504 - categorical_accuracy: 0.6198 - val_loss: 1.0355 - val_categorical_accuracy: 0.6255 - 482ms/epoch - 24ms/step
Epoch 115/1500
20/20 - 0s - loss: 1.0180 - categorical_accuracy: 0.6363 - val_loss: 1.0188 - val_categorical_accuracy: 0.6342 - 459ms/epoch - 23ms/step
Epoch 116/1500
20/20 - 0s - loss: 1.0116 - categorical_accuracy: 0.6385 - val_loss: 1.0084 - val_categorical_accuracy: 0.6417 - 488ms/epoch - 24ms/step
Epoch 117/1500
20/20 - 0s - loss: 1.0323 - categorical_accuracy: 0.6262 - val_loss: 1.0777 - val_categorical_accuracy: 0.6034 - 459ms/epoch - 23ms/step
Epoch 118/1500
20/20 - 1s - loss: 1.0539 - categorical_accuracy: 0.6173 - val_loss: 1.0063 - val_categorical_accuracy: 0.6413 - 503ms/epoch - 25ms/step
Epoch 119/1500
20/20 - 0s - loss: 1.0035 - categorical_accuracy: 0.6409 - val_loss: 0.9993 - val_categorical_accuracy: 0.6441 - 462ms/epoch - 23ms/step
Epoch 120/1500
20/20 - 1s - loss: 1.0031 - categorical_accuracy: 0.6409 - val_loss: 1.0149 - val_categorical_accuracy: 0.6322 - 534ms/epoch - 27ms/step
Epoch 121/1500
20/20 - 0s - loss: 1.0212 - categorical_accuracy: 0.6299 - val_loss: 0.9995 - val_categorical_accuracy: 0.6425 - 463ms/epoch - 23ms/step
Epoch 122/1500
20/20 - 0s - loss: 0.9935 - categorical_accuracy: 0.6445 - val_loss: 0.9851 - val_categorical_accuracy: 0.6500 - 474ms/epoch - 24ms/step
Epoch 123/1500
20/20 - 0s - loss: 0.9964 - categorical_accuracy: 0.6425 - val_loss: 1.0098 - val_categorical_accuracy: 0.6328 - 490ms/epoch - 24ms/step
Epoch 124/1500
20/20 - 0s - loss: 1.0008 - categorical_accuracy: 0.6387 - val_loss: 1.0328 - val_categorical_accuracy: 0.6207 - 469ms/epoch - 23ms/step
Epoch 125/1500
20/20 - 0s - loss: 1.0191 - categorical_accuracy: 0.6296 - val_loss: 0.9765 - val_categorical_accuracy: 0.6532 - 458ms/epoch - 23ms/step
Epoch 126/1500
20/20 - 0s - loss: 0.9731 - categorical_accuracy: 0.6535 - val_loss: 0.9790 - val_categorical_accuracy: 0.6519 - 488ms/epoch - 24ms/step
Epoch 127/1500
20/20 - 0s - loss: 0.9755 - categorical_accuracy: 0.6502 - val_loss: 0.9890 - val_categorical_accuracy: 0.6410 - 454ms/epoch - 23ms/step
Epoch 128/1500
20/20 - 0s - loss: 0.9739 - categorical_accuracy: 0.6501 - val_loss: 0.9673 - val_categorical_accuracy: 0.6556 - 458ms/epoch - 23ms/step
Epoch 129/1500
20/20 - 0s - loss: 0.9552 - categorical_accuracy: 0.6598 - val_loss: 0.9588 - val_categorical_accuracy: 0.6586 - 457ms/epoch - 23ms/step
Epoch 130/1500
20/20 - 0s - loss: 1.0059 - categorical_accuracy: 0.6341 - val_loss: 1.0837 - val_categorical_accuracy: 0.5980 - 458ms/epoch - 23ms/step
Epoch 131/1500
20/20 - 0s - loss: 0.9808 - categorical_accuracy: 0.6463 - val_loss: 0.9422 - val_categorical_accuracy: 0.6651 - 490ms/epoch - 25ms/step
Epoch 132/1500
20/20 - 0s - loss: 0.9398 - categorical_accuracy: 0.6659 - val_loss: 0.9377 - val_categorical_accuracy: 0.6669 - 458ms/epoch - 23ms/step
Epoch 133/1500
20/20 - 0s - loss: 0.9355 - categorical_accuracy: 0.6668 - val_loss: 0.9351 - val_categorical_accuracy: 0.6672 - 498ms/epoch - 25ms/step
Epoch 134/1500
20/20 - 0s - loss: 0.9929 - categorical_accuracy: 0.6368 - val_loss: 1.0111 - val_categorical_accuracy: 0.6277 - 450ms/epoch - 23ms/step
Epoch 135/1500
20/20 - 0s - loss: 0.9462 - categorical_accuracy: 0.6602 - val_loss: 0.9254 - val_categorical_accuracy: 0.6693 - 471ms/epoch - 24ms/step
Epoch 136/1500
20/20 - 0s - loss: 0.9253 - categorical_accuracy: 0.6702 - val_loss: 0.9278 - val_categorical_accuracy: 0.6692 - 460ms/epoch - 23ms/step
Epoch 137/1500
20/20 - 0s - loss: 0.9218 - categorical_accuracy: 0.6708 - val_loss: 0.9331 - val_categorical_accuracy: 0.6631 - 472ms/epoch - 24ms/step
Epoch 138/1500
20/20 - 0s - loss: 0.9800 - categorical_accuracy: 0.6405 - val_loss: 1.0020 - val_categorical_accuracy: 0.6276 - 456ms/epoch - 23ms/step
Epoch 139/1500
20/20 - 0s - loss: 0.9344 - categorical_accuracy: 0.6631 - val_loss: 0.9129 - val_categorical_accuracy: 0.6751 - 473ms/epoch - 24ms/step
Epoch 140/1500
20/20 - 0s - loss: 0.9129 - categorical_accuracy: 0.6736 - val_loss: 0.9100 - val_categorical_accuracy: 0.6747 - 473ms/epoch - 24ms/step
Epoch 141/1500
20/20 - 0s - loss: 0.9069 - categorical_accuracy: 0.6755 - val_loss: 0.9146 - val_categorical_accuracy: 0.6677 - 488ms/epoch - 24ms/step
Epoch 142/1500
20/20 - 0s - loss: 0.9250 - categorical_accuracy: 0.6635 - val_loss: 0.9809 - val_categorical_accuracy: 0.6379 - 474ms/epoch - 24ms/step
Epoch 143/1500
20/20 - 0s - loss: 0.9618 - categorical_accuracy: 0.6477 - val_loss: 0.9113 - val_categorical_accuracy: 0.6695 - 474ms/epoch - 24ms/step
Epoch 144/1500
20/20 - 0s - loss: 0.8996 - categorical_accuracy: 0.6770 - val_loss: 0.8934 - val_categorical_accuracy: 0.6774 - 468ms/epoch - 23ms/step
Epoch 145/1500
20/20 - 0s - loss: 0.8895 - categorical_accuracy: 0.6817 - val_loss: 0.8874 - val_categorical_accuracy: 0.6825 - 474ms/epoch - 24ms/step
Epoch 146/1500
20/20 - 0s - loss: 0.9241 - categorical_accuracy: 0.6645 - val_loss: 1.0698 - val_categorical_accuracy: 0.6019 - 476ms/epoch - 24ms/step
Epoch 147/1500
20/20 - 0s - loss: 0.9471 - categorical_accuracy: 0.6571 - val_loss: 0.8825 - val_categorical_accuracy: 0.6834 - 457ms/epoch - 23ms/step
Epoch 148/1500
20/20 - 0s - loss: 0.8800 - categorical_accuracy: 0.6844 - val_loss: 0.8784 - val_categorical_accuracy: 0.6860 - 472ms/epoch - 24ms/step
Epoch 149/1500
20/20 - 0s - loss: 0.8792 - categorical_accuracy: 0.6843 - val_loss: 0.8858 - val_categorical_accuracy: 0.6823 - 460ms/epoch - 23ms/step
Epoch 150/1500
20/20 - 0s - loss: 0.9020 - categorical_accuracy: 0.6718 - val_loss: 0.9276 - val_categorical_accuracy: 0.6595 - 458ms/epoch - 23ms/step
Epoch 151/1500
20/20 - 0s - loss: 0.9049 - categorical_accuracy: 0.6708 - val_loss: 0.8874 - val_categorical_accuracy: 0.6807 - 460ms/epoch - 23ms/step
Epoch 152/1500
20/20 - 0s - loss: 0.8764 - categorical_accuracy: 0.6840 - val_loss: 0.8712 - val_categorical_accuracy: 0.6841 - 483ms/epoch - 24ms/step
Epoch 153/1500
20/20 - 1s - loss: 0.8785 - categorical_accuracy: 0.6826 - val_loss: 0.9119 - val_categorical_accuracy: 0.6677 - 504ms/epoch - 25ms/step
Epoch 154/1500
20/20 - 1s - loss: 0.9029 - categorical_accuracy: 0.6677 - val_loss: 0.8849 - val_categorical_accuracy: 0.6833 - 508ms/epoch - 25ms/step
Epoch 155/1500
20/20 - 0s - loss: 0.8772 - categorical_accuracy: 0.6823 - val_loss: 0.8664 - val_categorical_accuracy: 0.6901 - 447ms/epoch - 22ms/step
Epoch 156/1500
20/20 - 0s - loss: 0.8813 - categorical_accuracy: 0.6804 - val_loss: 0.8905 - val_categorical_accuracy: 0.6793 - 469ms/epoch - 23ms/step
Epoch 157/1500
20/20 - 0s - loss: 0.8887 - categorical_accuracy: 0.6768 - val_loss: 0.8601 - val_categorical_accuracy: 0.6872 - 469ms/epoch - 23ms/step
Epoch 158/1500
20/20 - 0s - loss: 0.8559 - categorical_accuracy: 0.6908 - val_loss: 0.8539 - val_categorical_accuracy: 0.6913 - 463ms/epoch - 23ms/step
Epoch 159/1500
20/20 - 0s - loss: 0.8487 - categorical_accuracy: 0.6942 - val_loss: 0.8574 - val_categorical_accuracy: 0.6859 - 455ms/epoch - 23ms/step
Epoch 160/1500
20/20 - 0s - loss: 0.8690 - categorical_accuracy: 0.6845 - val_loss: 0.9077 - val_categorical_accuracy: 0.6689 - 474ms/epoch - 24ms/step
Epoch 161/1500
20/20 - 0s - loss: 0.9042 - categorical_accuracy: 0.6667 - val_loss: 0.8726 - val_categorical_accuracy: 0.6875 - 460ms/epoch - 23ms/step
Epoch 162/1500
20/20 - 0s - loss: 0.8606 - categorical_accuracy: 0.6870 - val_loss: 0.8499 - val_categorical_accuracy: 0.6963 - 458ms/epoch - 23ms/step
Epoch 163/1500
20/20 - 0s - loss: 0.8498 - categorical_accuracy: 0.6916 - val_loss: 0.8705 - val_categorical_accuracy: 0.6869 - 455ms/epoch - 23ms/step
Epoch 164/1500
20/20 - 0s - loss: 0.8637 - categorical_accuracy: 0.6842 - val_loss: 0.8579 - val_categorical_accuracy: 0.6938 - 492ms/epoch - 25ms/step
Epoch 165/1500
20/20 - 0s - loss: 0.8586 - categorical_accuracy: 0.6863 - val_loss: 0.8435 - val_categorical_accuracy: 0.6971 - 471ms/epoch - 24ms/step
Epoch 166/1500
20/20 - 0s - loss: 0.8468 - categorical_accuracy: 0.6931 - val_loss: 0.8615 - val_categorical_accuracy: 0.6848 - 470ms/epoch - 23ms/step
Epoch 167/1500
20/20 - 0s - loss: 0.8553 - categorical_accuracy: 0.6907 - val_loss: 0.8265 - val_categorical_accuracy: 0.6957 - 473ms/epoch - 24ms/step
Epoch 168/1500
20/20 - 0s - loss: 0.8334 - categorical_accuracy: 0.6974 - val_loss: 0.8671 - val_categorical_accuracy: 0.6731 - 458ms/epoch - 23ms/step
Epoch 169/1500
20/20 - 0s - loss: 0.8646 - categorical_accuracy: 0.6810 - val_loss: 0.8354 - val_categorical_accuracy: 0.6895 - 474ms/epoch - 24ms/step
Epoch 170/1500
20/20 - 0s - loss: 0.8189 - categorical_accuracy: 0.7041 - val_loss: 0.8239 - val_categorical_accuracy: 0.6972 - 461ms/epoch - 23ms/step
Epoch 171/1500
20/20 - 0s - loss: 0.8366 - categorical_accuracy: 0.6958 - val_loss: 0.8794 - val_categorical_accuracy: 0.6689 - 478ms/epoch - 24ms/step
Epoch 172/1500
20/20 - 0s - loss: 0.8672 - categorical_accuracy: 0.6805 - val_loss: 0.8137 - val_categorical_accuracy: 0.7045 - 459ms/epoch - 23ms/step
Epoch 173/1500
20/20 - 0s - loss: 0.8111 - categorical_accuracy: 0.7073 - val_loss: 0.8094 - val_categorical_accuracy: 0.7027 - 482ms/epoch - 24ms/step
Epoch 174/1500
20/20 - 0s - loss: 0.8313 - categorical_accuracy: 0.6966 - val_loss: 0.8447 - val_categorical_accuracy: 0.6838 - 459ms/epoch - 23ms/step
Epoch 175/1500
20/20 - 0s - loss: 0.8380 - categorical_accuracy: 0.6935 - val_loss: 0.8247 - val_categorical_accuracy: 0.6945 - 483ms/epoch - 24ms/step
Epoch 176/1500
20/20 - 0s - loss: 0.8186 - categorical_accuracy: 0.7026 - val_loss: 0.8429 - val_categorical_accuracy: 0.6911 - 456ms/epoch - 23ms/step
Epoch 177/1500
20/20 - 0s - loss: 0.8503 - categorical_accuracy: 0.6887 - val_loss: 0.8142 - val_categorical_accuracy: 0.7085 - 463ms/epoch - 23ms/step
Epoch 178/1500
20/20 - 0s - loss: 0.8090 - categorical_accuracy: 0.7071 - val_loss: 0.8099 - val_categorical_accuracy: 0.7108 - 452ms/epoch - 23ms/step
Epoch 179/1500
20/20 - 0s - loss: 0.8374 - categorical_accuracy: 0.6931 - val_loss: 0.8129 - val_categorical_accuracy: 0.7086 - 470ms/epoch - 24ms/step
Epoch 180/1500
20/20 - 0s - loss: 0.8009 - categorical_accuracy: 0.7099 - val_loss: 0.8034 - val_categorical_accuracy: 0.7063 - 461ms/epoch - 23ms/step
Epoch 181/1500
20/20 - 0s - loss: 0.8034 - categorical_accuracy: 0.7072 - val_loss: 0.8032 - val_categorical_accuracy: 0.7062 - 471ms/epoch - 24ms/step
Epoch 182/1500
20/20 - 0s - loss: 0.8079 - categorical_accuracy: 0.7050 - val_loss: 0.8068 - val_categorical_accuracy: 0.7054 - 470ms/epoch - 24ms/step
Epoch 183/1500
20/20 - 0s - loss: 0.8005 - categorical_accuracy: 0.7098 - val_loss: 0.8064 - val_categorical_accuracy: 0.7053 - 477ms/epoch - 24ms/step
Epoch 184/1500
20/20 - 1s - loss: 0.7848 - categorical_accuracy: 0.7149 - val_loss: 0.8101 - val_categorical_accuracy: 0.7097 - 500ms/epoch - 25ms/step
Epoch 185/1500
20/20 - 0s - loss: 0.8567 - categorical_accuracy: 0.6840 - val_loss: 0.8058 - val_categorical_accuracy: 0.7116 - 463ms/epoch - 23ms/step
Epoch 186/1500
20/20 - 0s - loss: 0.7805 - categorical_accuracy: 0.7181 - val_loss: 0.7787 - val_categorical_accuracy: 0.7181 - 463ms/epoch - 23ms/step
Epoch 187/1500
20/20 - 0s - loss: 0.7923 - categorical_accuracy: 0.7106 - val_loss: 0.8156 - val_categorical_accuracy: 0.6976 - 451ms/epoch - 23ms/step
Epoch 188/1500
20/20 - 1s - loss: 0.8076 - categorical_accuracy: 0.7032 - val_loss: 0.7924 - val_categorical_accuracy: 0.7115 - 515ms/epoch - 26ms/step
Epoch 189/1500
20/20 - 0s - loss: 0.7883 - categorical_accuracy: 0.7134 - val_loss: 0.8035 - val_categorical_accuracy: 0.7099 - 455ms/epoch - 23ms/step
Epoch 190/1500
20/20 - 0s - loss: 0.8110 - categorical_accuracy: 0.7036 - val_loss: 0.8008 - val_categorical_accuracy: 0.7143 - 472ms/epoch - 24ms/step
Epoch 191/1500
20/20 - 0s - loss: 0.7783 - categorical_accuracy: 0.7176 - val_loss: 0.7662 - val_categorical_accuracy: 0.7227 - 456ms/epoch - 23ms/step
Epoch 192/1500
20/20 - 0s - loss: 0.7683 - categorical_accuracy: 0.7218 - val_loss: 0.7670 - val_categorical_accuracy: 0.7278 - 472ms/epoch - 24ms/step
Epoch 193/1500
20/20 - 0s - loss: 0.8192 - categorical_accuracy: 0.7010 - val_loss: 0.7630 - val_categorical_accuracy: 0.7285 - 460ms/epoch - 23ms/step
Epoch 194/1500
20/20 - 0s - loss: 0.7557 - categorical_accuracy: 0.7276 - val_loss: 0.7716 - val_categorical_accuracy: 0.7196 - 462ms/epoch - 23ms/step
Epoch 195/1500
20/20 - 0s - loss: 0.7751 - categorical_accuracy: 0.7168 - val_loss: 0.8277 - val_categorical_accuracy: 0.6959 - 460ms/epoch - 23ms/step
Epoch 196/1500
20/20 - 0s - loss: 0.7899 - categorical_accuracy: 0.7096 - val_loss: 0.7710 - val_categorical_accuracy: 0.7191 - 472ms/epoch - 24ms/step
Epoch 197/1500
20/20 - 0s - loss: 0.7612 - categorical_accuracy: 0.7228 - val_loss: 0.7499 - val_categorical_accuracy: 0.7313 - 454ms/epoch - 23ms/step
Epoch 198/1500
20/20 - 0s - loss: 0.7729 - categorical_accuracy: 0.7184 - val_loss: 0.7813 - val_categorical_accuracy: 0.7203 - 470ms/epoch - 24ms/step
Epoch 199/1500
20/20 - 0s - loss: 0.7641 - categorical_accuracy: 0.7223 - val_loss: 0.7462 - val_categorical_accuracy: 0.7342 - 458ms/epoch - 23ms/step
Epoch 200/1500
20/20 - 0s - loss: 0.7568 - categorical_accuracy: 0.7259 - val_loss: 0.7745 - val_categorical_accuracy: 0.7236 - 463ms/epoch - 23ms/step
Epoch 201/1500
20/20 - 0s - loss: 0.7912 - categorical_accuracy: 0.7118 - val_loss: 0.8003 - val_categorical_accuracy: 0.7085 - 469ms/epoch - 23ms/step
Epoch 202/1500
20/20 - 0s - loss: 0.7937 - categorical_accuracy: 0.7064 - val_loss: 0.7576 - val_categorical_accuracy: 0.7185 - 447ms/epoch - 22ms/step
Epoch 203/1500
20/20 - 0s - loss: 0.7406 - categorical_accuracy: 0.7315 - val_loss: 0.7663 - val_categorical_accuracy: 0.7162 - 458ms/epoch - 23ms/step
Epoch 204/1500
20/20 - 0s - loss: 0.7496 - categorical_accuracy: 0.7252 - val_loss: 0.7496 - val_categorical_accuracy: 0.7234 - 455ms/epoch - 23ms/step
Epoch 205/1500
20/20 - 1s - loss: 0.7585 - categorical_accuracy: 0.7201 - val_loss: 0.7597 - val_categorical_accuracy: 0.7173 - 553ms/epoch - 28ms/step
Epoch 206/1500
20/20 - 0s - loss: 0.7437 - categorical_accuracy: 0.7273 - val_loss: 0.7388 - val_categorical_accuracy: 0.7298 - 458ms/epoch - 23ms/step
Epoch 207/1500
20/20 - 0s - loss: 0.7449 - categorical_accuracy: 0.7274 - val_loss: 0.7861 - val_categorical_accuracy: 0.7084 - 472ms/epoch - 24ms/step
Epoch 208/1500
20/20 - 0s - loss: 0.8190 - categorical_accuracy: 0.7012 - val_loss: 0.7375 - val_categorical_accuracy: 0.7289 - 460ms/epoch - 23ms/step
Epoch 209/1500
20/20 - 0s - loss: 0.7200 - categorical_accuracy: 0.7397 - val_loss: 0.7178 - val_categorical_accuracy: 0.7407 - 476ms/epoch - 24ms/step
Epoch 210/1500
20/20 - 0s - loss: 0.7179 - categorical_accuracy: 0.7401 - val_loss: 0.7409 - val_categorical_accuracy: 0.7235 - 456ms/epoch - 23ms/step
Epoch 211/1500
20/20 - 0s - loss: 0.8149 - categorical_accuracy: 0.6974 - val_loss: 0.7778 - val_categorical_accuracy: 0.7103 - 472ms/epoch - 24ms/step
Epoch 212/1500
20/20 - 0s - loss: 0.7317 - categorical_accuracy: 0.7320 - val_loss: 0.7312 - val_categorical_accuracy: 0.7330 - 469ms/epoch - 23ms/step
Epoch 213/1500
20/20 - 0s - loss: 0.7224 - categorical_accuracy: 0.7373 - val_loss: 0.7249 - val_categorical_accuracy: 0.7404 - 472ms/epoch - 24ms/step
Epoch 214/1500
20/20 - 0s - loss: 0.7434 - categorical_accuracy: 0.7278 - val_loss: 0.7594 - val_categorical_accuracy: 0.7277 - 460ms/epoch - 23ms/step
Epoch 215/1500
20/20 - 0s - loss: 0.7367 - categorical_accuracy: 0.7314 - val_loss: 0.7252 - val_categorical_accuracy: 0.7355 - 459ms/epoch - 23ms/step
Epoch 216/1500
20/20 - 0s - loss: 0.7434 - categorical_accuracy: 0.7260 - val_loss: 0.7632 - val_categorical_accuracy: 0.7200 - 457ms/epoch - 23ms/step
Epoch 217/1500
20/20 - 0s - loss: 0.7243 - categorical_accuracy: 0.7347 - val_loss: 0.7465 - val_categorical_accuracy: 0.7185 - 474ms/epoch - 24ms/step
Epoch 218/1500
20/20 - 0s - loss: 0.7499 - categorical_accuracy: 0.7238 - val_loss: 0.7304 - val_categorical_accuracy: 0.7281 - 492ms/epoch - 25ms/step
Epoch 219/1500
20/20 - 1s - loss: 0.7079 - categorical_accuracy: 0.7424 - val_loss: 0.7013 - val_categorical_accuracy: 0.7434 - 503ms/epoch - 25ms/step
Epoch 220/1500
20/20 - 0s - loss: 0.7115 - categorical_accuracy: 0.7384 - val_loss: 0.7500 - val_categorical_accuracy: 0.7184 - 498ms/epoch - 25ms/step
Epoch 221/1500
20/20 - 0s - loss: 0.7807 - categorical_accuracy: 0.7090 - val_loss: 0.7887 - val_categorical_accuracy: 0.7149 - 480ms/epoch - 24ms/step
Epoch 222/1500
20/20 - 1s - loss: 0.7243 - categorical_accuracy: 0.7363 - val_loss: 0.6971 - val_categorical_accuracy: 0.7472 - 512ms/epoch - 26ms/step
Epoch 223/1500
20/20 - 0s - loss: 0.6905 - categorical_accuracy: 0.7498 - val_loss: 0.6989 - val_categorical_accuracy: 0.7423 - 490ms/epoch - 24ms/step
Epoch 224/1500
20/20 - 1s - loss: 0.7079 - categorical_accuracy: 0.7397 - val_loss: 0.7685 - val_categorical_accuracy: 0.7087 - 509ms/epoch - 25ms/step
Epoch 225/1500
20/20 - 0s - loss: 0.7877 - categorical_accuracy: 0.7088 - val_loss: 0.7263 - val_categorical_accuracy: 0.7285 - 500ms/epoch - 25ms/step
Epoch 226/1500
20/20 - 1s - loss: 0.6942 - categorical_accuracy: 0.7482 - val_loss: 0.6921 - val_categorical_accuracy: 0.7454 - 515ms/epoch - 26ms/step
Epoch 227/1500
20/20 - 0s - loss: 0.7094 - categorical_accuracy: 0.7405 - val_loss: 0.7898 - val_categorical_accuracy: 0.7027 - 492ms/epoch - 25ms/step
Epoch 228/1500
20/20 - 0s - loss: 0.7352 - categorical_accuracy: 0.7286 - val_loss: 0.6891 - val_categorical_accuracy: 0.7484 - 498ms/epoch - 25ms/step
Epoch 229/1500
20/20 - 1s - loss: 0.6875 - categorical_accuracy: 0.7501 - val_loss: 0.6974 - val_categorical_accuracy: 0.7429 - 506ms/epoch - 25ms/step
Epoch 230/1500
20/20 - 0s - loss: 0.7204 - categorical_accuracy: 0.7356 - val_loss: 0.7550 - val_categorical_accuracy: 0.7168 - 500ms/epoch - 25ms/step
Epoch 231/1500
20/20 - 0s - loss: 0.7081 - categorical_accuracy: 0.7383 - val_loss: 0.6941 - val_categorical_accuracy: 0.7458 - 497ms/epoch - 25ms/step
Epoch 232/1500
20/20 - 1s - loss: 0.6868 - categorical_accuracy: 0.7464 - val_loss: 0.7087 - val_categorical_accuracy: 0.7384 - 503ms/epoch - 25ms/step
Epoch 233/1500
20/20 - 0s - loss: 0.7330 - categorical_accuracy: 0.7270 - val_loss: 0.7787 - val_categorical_accuracy: 0.7228 - 494ms/epoch - 25ms/step
Epoch 234/1500
20/20 - 1s - loss: 0.7499 - categorical_accuracy: 0.7275 - val_loss: 0.6811 - val_categorical_accuracy: 0.7532 - 500ms/epoch - 25ms/step
Epoch 235/1500
20/20 - 1s - loss: 0.6746 - categorical_accuracy: 0.7542 - val_loss: 0.6784 - val_categorical_accuracy: 0.7486 - 502ms/epoch - 25ms/step
Epoch 236/1500
20/20 - 1s - loss: 0.6872 - categorical_accuracy: 0.7448 - val_loss: 0.6985 - val_categorical_accuracy: 0.7364 - 502ms/epoch - 25ms/step
Epoch 237/1500
20/20 - 1s - loss: 0.6936 - categorical_accuracy: 0.7410 - val_loss: 0.6781 - val_categorical_accuracy: 0.7487 - 500ms/epoch - 25ms/step
Epoch 238/1500
20/20 - 1s - loss: 0.6828 - categorical_accuracy: 0.7481 - val_loss: 0.7234 - val_categorical_accuracy: 0.7336 - 502ms/epoch - 25ms/step
Epoch 239/1500
20/20 - 0s - loss: 0.7543 - categorical_accuracy: 0.7191 - val_loss: 0.6719 - val_categorical_accuracy: 0.7581 - 500ms/epoch - 25ms/step
Epoch 240/1500
20/20 - 1s - loss: 0.6671 - categorical_accuracy: 0.7563 - val_loss: 0.6636 - val_categorical_accuracy: 0.7576 - 505ms/epoch - 25ms/step
Epoch 241/1500
20/20 - 1s - loss: 0.6684 - categorical_accuracy: 0.7553 - val_loss: 0.6877 - val_categorical_accuracy: 0.7451 - 502ms/epoch - 25ms/step
Epoch 242/1500
20/20 - 1s - loss: 0.7061 - categorical_accuracy: 0.7365 - val_loss: 0.6875 - val_categorical_accuracy: 0.7502 - 502ms/epoch - 25ms/step
Epoch 243/1500
20/20 - 1s - loss: 0.6779 - categorical_accuracy: 0.7514 - val_loss: 0.7142 - val_categorical_accuracy: 0.7415 - 500ms/epoch - 25ms/step
Epoch 244/1500
20/20 - 1s - loss: 0.7861 - categorical_accuracy: 0.7131 - val_loss: 0.6692 - val_categorical_accuracy: 0.7541 - 503ms/epoch - 25ms/step
Epoch 245/1500
20/20 - 1s - loss: 0.6573 - categorical_accuracy: 0.7598 - val_loss: 0.6643 - val_categorical_accuracy: 0.7578 - 507ms/epoch - 25ms/step
Epoch 246/1500
20/20 - 1s - loss: 0.6683 - categorical_accuracy: 0.7543 - val_loss: 0.6878 - val_categorical_accuracy: 0.7519 - 506ms/epoch - 25ms/step
Epoch 247/1500
20/20 - 1s - loss: 0.6670 - categorical_accuracy: 0.7552 - val_loss: 0.6690 - val_categorical_accuracy: 0.7601 - 504ms/epoch - 25ms/step
Epoch 248/1500
20/20 - 1s - loss: 0.6709 - categorical_accuracy: 0.7539 - val_loss: 0.6707 - val_categorical_accuracy: 0.7577 - 533ms/epoch - 27ms/step
Epoch 249/1500
20/20 - 1s - loss: 0.7058 - categorical_accuracy: 0.7395 - val_loss: 0.7024 - val_categorical_accuracy: 0.7461 - 514ms/epoch - 26ms/step
Epoch 250/1500
20/20 - 1s - loss: 0.6809 - categorical_accuracy: 0.7475 - val_loss: 0.6965 - val_categorical_accuracy: 0.7382 - 517ms/epoch - 26ms/step
Epoch 251/1500
20/20 - 1s - loss: 0.6890 - categorical_accuracy: 0.7411 - val_loss: 0.6902 - val_categorical_accuracy: 0.7435 - 519ms/epoch - 26ms/step
Epoch 252/1500
20/20 - 1s - loss: 0.6695 - categorical_accuracy: 0.7522 - val_loss: 0.6663 - val_categorical_accuracy: 0.7571 - 501ms/epoch - 25ms/step
Epoch 253/1500
20/20 - 1s - loss: 0.6605 - categorical_accuracy: 0.7581 - val_loss: 0.6728 - val_categorical_accuracy: 0.7556 - 530ms/epoch - 26ms/step
Epoch 254/1500
20/20 - 1s - loss: 0.6622 - categorical_accuracy: 0.7575 - val_loss: 0.6938 - val_categorical_accuracy: 0.7485 - 501ms/epoch - 25ms/step
Epoch 255/1500
20/20 - 1s - loss: 0.6809 - categorical_accuracy: 0.7474 - val_loss: 0.6548 - val_categorical_accuracy: 0.7648 - 514ms/epoch - 26ms/step
Epoch 256/1500
20/20 - 1s - loss: 0.6865 - categorical_accuracy: 0.7435 - val_loss: 0.7042 - val_categorical_accuracy: 0.7369 - 504ms/epoch - 25ms/step
Epoch 257/1500
20/20 - 1s - loss: 0.6594 - categorical_accuracy: 0.7553 - val_loss: 0.6540 - val_categorical_accuracy: 0.7611 - 550ms/epoch - 27ms/step
Epoch 258/1500
20/20 - 1s - loss: 0.6529 - categorical_accuracy: 0.7588 - val_loss: 0.6758 - val_categorical_accuracy: 0.7478 - 514ms/epoch - 26ms/step
Epoch 259/1500
20/20 - 1s - loss: 0.6970 - categorical_accuracy: 0.7425 - val_loss: 0.7194 - val_categorical_accuracy: 0.7319 - 514ms/epoch - 26ms/step
Epoch 260/1500
20/20 - 0s - loss: 0.6642 - categorical_accuracy: 0.7556 - val_loss: 0.6425 - val_categorical_accuracy: 0.7603 - 500ms/epoch - 25ms/step
Epoch 261/1500
20/20 - 1s - loss: 0.6404 - categorical_accuracy: 0.7637 - val_loss: 0.6480 - val_categorical_accuracy: 0.7579 - 527ms/epoch - 26ms/step
Epoch 262/1500
20/20 - 1s - loss: 0.6468 - categorical_accuracy: 0.7598 - val_loss: 0.6602 - val_categorical_accuracy: 0.7513 - 532ms/epoch - 27ms/step
Epoch 263/1500
20/20 - 1s - loss: 0.6397 - categorical_accuracy: 0.7635 - val_loss: 0.6373 - val_categorical_accuracy: 0.7622 - 543ms/epoch - 27ms/step
Epoch 264/1500
20/20 - 1s - loss: 0.6756 - categorical_accuracy: 0.7480 - val_loss: 0.7846 - val_categorical_accuracy: 0.7071 - 521ms/epoch - 26ms/step
Epoch 265/1500
20/20 - 1s - loss: 1.1629 - categorical_accuracy: 0.6585 - val_loss: 0.6625 - val_categorical_accuracy: 0.7578 - 519ms/epoch - 26ms/step
Epoch 266/1500
20/20 - 1s - loss: 0.6479 - categorical_accuracy: 0.7646 - val_loss: 0.6436 - val_categorical_accuracy: 0.7647 - 533ms/epoch - 27ms/step
Epoch 267/1500
20/20 - 1s - loss: 0.6348 - categorical_accuracy: 0.7683 - val_loss: 0.6352 - val_categorical_accuracy: 0.7682 - 539ms/epoch - 27ms/step
Epoch 268/1500
20/20 - 1s - loss: 0.6284 - categorical_accuracy: 0.7700 - val_loss: 0.6312 - val_categorical_accuracy: 0.7686 - 504ms/epoch - 25ms/step
Epoch 269/1500
20/20 - 1s - loss: 0.6247 - categorical_accuracy: 0.7716 - val_loss: 0.6260 - val_categorical_accuracy: 0.7693 - 534ms/epoch - 27ms/step
Epoch 270/1500
20/20 - 1s - loss: 0.6267 - categorical_accuracy: 0.7698 - val_loss: 0.6385 - val_categorical_accuracy: 0.7611 - 523ms/epoch - 26ms/step
Epoch 271/1500
20/20 - 0s - loss: 0.6420 - categorical_accuracy: 0.7634 - val_loss: 0.6638 - val_categorical_accuracy: 0.7493 - 495ms/epoch - 25ms/step
Epoch 272/1500
20/20 - 1s - loss: 0.7489 - categorical_accuracy: 0.7253 - val_loss: 0.6422 - val_categorical_accuracy: 0.7635 - 523ms/epoch - 26ms/step
Epoch 273/1500
20/20 - 1s - loss: 0.6230 - categorical_accuracy: 0.7707 - val_loss: 0.6237 - val_categorical_accuracy: 0.7717 - 518ms/epoch - 26ms/step
Epoch 274/1500
20/20 - 1s - loss: 0.6259 - categorical_accuracy: 0.7687 - val_loss: 0.6441 - val_categorical_accuracy: 0.7609 - 534ms/epoch - 27ms/step
Epoch 275/1500
20/20 - 1s - loss: 0.6433 - categorical_accuracy: 0.7592 - val_loss: 0.6332 - val_categorical_accuracy: 0.7677 - 535ms/epoch - 27ms/step
Epoch 276/1500
20/20 - 1s - loss: 0.6295 - categorical_accuracy: 0.7674 - val_loss: 0.6335 - val_categorical_accuracy: 0.7701 - 520ms/epoch - 26ms/step
Epoch 277/1500
20/20 - 0s - loss: 0.6294 - categorical_accuracy: 0.7674 - val_loss: 0.6332 - val_categorical_accuracy: 0.7676 - 474ms/epoch - 24ms/step
Epoch 278/1500
20/20 - 0s - loss: 0.6397 - categorical_accuracy: 0.7612 - val_loss: 0.6590 - val_categorical_accuracy: 0.7537 - 481ms/epoch - 24ms/step
Epoch 279/1500
20/20 - 0s - loss: 0.6386 - categorical_accuracy: 0.7611 - val_loss: 0.6294 - val_categorical_accuracy: 0.7693 - 460ms/epoch - 23ms/step
Epoch 280/1500
20/20 - 0s - loss: 0.6283 - categorical_accuracy: 0.7665 - val_loss: 0.6449 - val_categorical_accuracy: 0.7606 - 490ms/epoch - 24ms/step
Epoch 281/1500
20/20 - 0s - loss: 0.6431 - categorical_accuracy: 0.7592 - val_loss: 0.6351 - val_categorical_accuracy: 0.7639 - 490ms/epoch - 25ms/step
Epoch 282/1500
20/20 - 1s - loss: 0.6332 - categorical_accuracy: 0.7646 - val_loss: 0.6879 - val_categorical_accuracy: 0.7395 - 561ms/epoch - 28ms/step
Epoch 283/1500
20/20 - 1s - loss: 0.7853 - categorical_accuracy: 0.7159 - val_loss: 0.6152 - val_categorical_accuracy: 0.7721 - 527ms/epoch - 26ms/step
Epoch 284/1500
20/20 - 1s - loss: 0.6074 - categorical_accuracy: 0.7767 - val_loss: 0.6117 - val_categorical_accuracy: 0.7759 - 515ms/epoch - 26ms/step
Epoch 285/1500
20/20 - 0s - loss: 0.6064 - categorical_accuracy: 0.7768 - val_loss: 0.6153 - val_categorical_accuracy: 0.7735 - 461ms/epoch - 23ms/step
Epoch 286/1500
20/20 - 0s - loss: 0.6081 - categorical_accuracy: 0.7758 - val_loss: 0.6076 - val_categorical_accuracy: 0.7773 - 475ms/epoch - 24ms/step
Epoch 287/1500
20/20 - 0s - loss: 0.6117 - categorical_accuracy: 0.7730 - val_loss: 0.6540 - val_categorical_accuracy: 0.7531 - 460ms/epoch - 23ms/step
Epoch 288/1500
20/20 - 0s - loss: 0.6372 - categorical_accuracy: 0.7605 - val_loss: 0.6346 - val_categorical_accuracy: 0.7647 - 474ms/epoch - 24ms/step
Epoch 289/1500
20/20 - 1s - loss: 0.6221 - categorical_accuracy: 0.7683 - val_loss: 0.6267 - val_categorical_accuracy: 0.7701 - 503ms/epoch - 25ms/step
Epoch 290/1500
20/20 - 0s - loss: 0.6472 - categorical_accuracy: 0.7612 - val_loss: 0.8101 - val_categorical_accuracy: 0.7015 - 473ms/epoch - 24ms/step
Epoch 291/1500
20/20 - 0s - loss: 0.6753 - categorical_accuracy: 0.7528 - val_loss: 0.5993 - val_categorical_accuracy: 0.7789 - 459ms/epoch - 23ms/step
Epoch 292/1500
20/20 - 0s - loss: 0.5959 - categorical_accuracy: 0.7801 - val_loss: 0.6102 - val_categorical_accuracy: 0.7766 - 472ms/epoch - 24ms/step
Epoch 293/1500
20/20 - 0s - loss: 0.6137 - categorical_accuracy: 0.7706 - val_loss: 0.6193 - val_categorical_accuracy: 0.7717 - 461ms/epoch - 23ms/step
Epoch 294/1500
20/20 - 0s - loss: 0.6122 - categorical_accuracy: 0.7732 - val_loss: 0.6009 - val_categorical_accuracy: 0.7793 - 465ms/epoch - 23ms/step
Epoch 295/1500
20/20 - 0s - loss: 0.6152 - categorical_accuracy: 0.7707 - val_loss: 0.6306 - val_categorical_accuracy: 0.7652 - 477ms/epoch - 24ms/step
Epoch 296/1500
20/20 - 0s - loss: 0.6220 - categorical_accuracy: 0.7682 - val_loss: 0.6317 - val_categorical_accuracy: 0.7663 - 455ms/epoch - 23ms/step
Epoch 297/1500
20/20 - 0s - loss: 0.6081 - categorical_accuracy: 0.7752 - val_loss: 0.6012 - val_categorical_accuracy: 0.7796 - 474ms/epoch - 24ms/step
Epoch 298/1500
20/20 - 0s - loss: 0.6019 - categorical_accuracy: 0.7773 - val_loss: 0.6120 - val_categorical_accuracy: 0.7717 - 458ms/epoch - 23ms/step
Epoch 299/1500
20/20 - 0s - loss: 0.6093 - categorical_accuracy: 0.7740 - val_loss: 0.6210 - val_categorical_accuracy: 0.7689 - 475ms/epoch - 24ms/step
Epoch 300/1500
20/20 - 0s - loss: 0.6164 - categorical_accuracy: 0.7712 - val_loss: 0.6242 - val_categorical_accuracy: 0.7674 - 447ms/epoch - 22ms/step
Epoch 301/1500
20/20 - 0s - loss: 0.6089 - categorical_accuracy: 0.7748 - val_loss: 0.6739 - val_categorical_accuracy: 0.7534 - 476ms/epoch - 24ms/step
Epoch 302/1500
20/20 - 0s - loss: 0.7787 - categorical_accuracy: 0.7256 - val_loss: 0.5931 - val_categorical_accuracy: 0.7818 - 469ms/epoch - 23ms/step
Epoch 303/1500
20/20 - 0s - loss: 0.5830 - categorical_accuracy: 0.7857 - val_loss: 0.5886 - val_categorical_accuracy: 0.7846 - 474ms/epoch - 24ms/step
Epoch 304/1500
20/20 - 0s - loss: 0.5795 - categorical_accuracy: 0.7866 - val_loss: 0.5848 - val_categorical_accuracy: 0.7841 - 459ms/epoch - 23ms/step
Epoch 305/1500
20/20 - 0s - loss: 0.5790 - categorical_accuracy: 0.7875 - val_loss: 0.5883 - val_categorical_accuracy: 0.7828 - 476ms/epoch - 24ms/step
Epoch 306/1500
20/20 - 0s - loss: 0.6114 - categorical_accuracy: 0.7747 - val_loss: 0.6828 - val_categorical_accuracy: 0.7472 - 453ms/epoch - 23ms/step
Epoch 307/1500
20/20 - 0s - loss: 0.6696 - categorical_accuracy: 0.7521 - val_loss: 0.6065 - val_categorical_accuracy: 0.7711 - 468ms/epoch - 23ms/step
Epoch 308/1500
20/20 - 0s - loss: 0.5895 - categorical_accuracy: 0.7817 - val_loss: 0.5916 - val_categorical_accuracy: 0.7782 - 482ms/epoch - 24ms/step
Epoch 309/1500
20/20 - 0s - loss: 0.5905 - categorical_accuracy: 0.7801 - val_loss: 0.6329 - val_categorical_accuracy: 0.7598 - 496ms/epoch - 25ms/step
Epoch 310/1500
20/20 - 1s - loss: 0.6164 - categorical_accuracy: 0.7693 - val_loss: 0.6026 - val_categorical_accuracy: 0.7733 - 508ms/epoch - 25ms/step
Epoch 311/1500
20/20 - 0s - loss: 0.6007 - categorical_accuracy: 0.7756 - val_loss: 0.5860 - val_categorical_accuracy: 0.7807 - 493ms/epoch - 25ms/step
Epoch 312/1500
20/20 - 1s - loss: 0.5780 - categorical_accuracy: 0.7881 - val_loss: 0.5756 - val_categorical_accuracy: 0.7881 - 513ms/epoch - 26ms/step
Epoch 313/1500
20/20 - 0s - loss: 0.5694 - categorical_accuracy: 0.7905 - val_loss: 0.5870 - val_categorical_accuracy: 0.7788 - 474ms/epoch - 24ms/step
Epoch 314/1500
20/20 - 0s - loss: 0.6213 - categorical_accuracy: 0.7674 - val_loss: 0.6009 - val_categorical_accuracy: 0.7738 - 480ms/epoch - 24ms/step
Epoch 315/1500
20/20 - 0s - loss: 0.5862 - categorical_accuracy: 0.7830 - val_loss: 0.5870 - val_categorical_accuracy: 0.7817 - 458ms/epoch - 23ms/step
Epoch 316/1500
20/20 - 0s - loss: 0.6071 - categorical_accuracy: 0.7785 - val_loss: 0.7699 - val_categorical_accuracy: 0.7236 - 466ms/epoch - 23ms/step
Epoch 317/1500
20/20 - 0s - loss: 0.7299 - categorical_accuracy: 0.7382 - val_loss: 0.5750 - val_categorical_accuracy: 0.7876 - 462ms/epoch - 23ms/step
Epoch 318/1500
20/20 - 1s - loss: 0.5677 - categorical_accuracy: 0.7909 - val_loss: 0.5761 - val_categorical_accuracy: 0.7848 - 531ms/epoch - 27ms/step
Epoch 319/1500
20/20 - 0s - loss: 0.5645 - categorical_accuracy: 0.7920 - val_loss: 0.5702 - val_categorical_accuracy: 0.7909 - 469ms/epoch - 23ms/step
Epoch 320/1500
20/20 - 0s - loss: 0.5741 - categorical_accuracy: 0.7880 - val_loss: 0.6286 - val_categorical_accuracy: 0.7635 - 484ms/epoch - 24ms/step
Epoch 321/1500
20/20 - 0s - loss: 0.6214 - categorical_accuracy: 0.7672 - val_loss: 0.5896 - val_categorical_accuracy: 0.7784 - 475ms/epoch - 24ms/step
Epoch 322/1500
20/20 - 0s - loss: 0.5737 - categorical_accuracy: 0.7882 - val_loss: 0.5904 - val_categorical_accuracy: 0.7781 - 471ms/epoch - 24ms/step
Epoch 323/1500
20/20 - 0s - loss: 0.5889 - categorical_accuracy: 0.7819 - val_loss: 0.5819 - val_categorical_accuracy: 0.7817 - 479ms/epoch - 24ms/step
Epoch 324/1500
20/20 - 0s - loss: 0.5739 - categorical_accuracy: 0.7884 - val_loss: 0.5721 - val_categorical_accuracy: 0.7853 - 471ms/epoch - 24ms/step
Epoch 325/1500
20/20 - 0s - loss: 0.5590 - categorical_accuracy: 0.7943 - val_loss: 0.5813 - val_categorical_accuracy: 0.7822 - 460ms/epoch - 23ms/step
Epoch 326/1500
20/20 - 0s - loss: 0.5958 - categorical_accuracy: 0.7763 - val_loss: 0.6026 - val_categorical_accuracy: 0.7730 - 469ms/epoch - 23ms/step
Epoch 327/1500
20/20 - 0s - loss: 0.5854 - categorical_accuracy: 0.7816 - val_loss: 0.5744 - val_categorical_accuracy: 0.7862 - 458ms/epoch - 23ms/step
Epoch 328/1500
20/20 - 0s - loss: 0.5644 - categorical_accuracy: 0.7910 - val_loss: 0.5602 - val_categorical_accuracy: 0.7924 - 483ms/epoch - 24ms/step
Epoch 329/1500
20/20 - 0s - loss: 0.5512 - categorical_accuracy: 0.7974 - val_loss: 0.5702 - val_categorical_accuracy: 0.7862 - 457ms/epoch - 23ms/step
Epoch 330/1500
20/20 - 0s - loss: 0.5940 - categorical_accuracy: 0.7785 - val_loss: 0.6067 - val_categorical_accuracy: 0.7718 - 476ms/epoch - 24ms/step
Epoch 331/1500
20/20 - 0s - loss: 0.5850 - categorical_accuracy: 0.7843 - val_loss: 0.5832 - val_categorical_accuracy: 0.7797 - 475ms/epoch - 24ms/step
Epoch 332/1500
20/20 - 1s - loss: 0.5736 - categorical_accuracy: 0.7871 - val_loss: 0.5716 - val_categorical_accuracy: 0.7864 - 513ms/epoch - 26ms/step
Epoch 333/1500
20/20 - 1s - loss: 0.5730 - categorical_accuracy: 0.7882 - val_loss: 0.6102 - val_categorical_accuracy: 0.7716 - 506ms/epoch - 25ms/step
Epoch 334/1500
20/20 - 0s - loss: 0.6858 - categorical_accuracy: 0.7537 - val_loss: 0.7713 - val_categorical_accuracy: 0.7189 - 477ms/epoch - 24ms/step
Epoch 335/1500
20/20 - 0s - loss: 0.5821 - categorical_accuracy: 0.7878 - val_loss: 0.5594 - val_categorical_accuracy: 0.7920 - 459ms/epoch - 23ms/step
Epoch 336/1500
20/20 - 0s - loss: 0.5486 - categorical_accuracy: 0.7989 - val_loss: 0.5602 - val_categorical_accuracy: 0.7912 - 454ms/epoch - 23ms/step
Epoch 337/1500
20/20 - 0s - loss: 0.5591 - categorical_accuracy: 0.7948 - val_loss: 0.5588 - val_categorical_accuracy: 0.7918 - 476ms/epoch - 24ms/step
Epoch 338/1500
20/20 - 0s - loss: 0.5788 - categorical_accuracy: 0.7843 - val_loss: 0.6198 - val_categorical_accuracy: 0.7662 - 472ms/epoch - 24ms/step
Epoch 339/1500
20/20 - 0s - loss: 0.5727 - categorical_accuracy: 0.7876 - val_loss: 0.5559 - val_categorical_accuracy: 0.7944 - 476ms/epoch - 24ms/step
Epoch 340/1500
20/20 - 0s - loss: 0.5426 - categorical_accuracy: 0.8018 - val_loss: 0.5621 - val_categorical_accuracy: 0.7897 - 460ms/epoch - 23ms/step
Epoch 341/1500
20/20 - 0s - loss: 0.6422 - categorical_accuracy: 0.7692 - val_loss: 1.7310 - val_categorical_accuracy: 0.5694 - 483ms/epoch - 24ms/step
Epoch 342/1500
20/20 - 0s - loss: 1.0280 - categorical_accuracy: 0.7142 - val_loss: 0.5716 - val_categorical_accuracy: 0.7924 - 462ms/epoch - 23ms/step
Epoch 343/1500
20/20 - 0s - loss: 0.5579 - categorical_accuracy: 0.7987 - val_loss: 0.5594 - val_categorical_accuracy: 0.7963 - 477ms/epoch - 24ms/step
Epoch 344/1500
20/20 - 0s - loss: 0.5479 - categorical_accuracy: 0.8021 - val_loss: 0.5516 - val_categorical_accuracy: 0.7988 - 459ms/epoch - 23ms/step
Epoch 345/1500
20/20 - 0s - loss: 0.5425 - categorical_accuracy: 0.8026 - val_loss: 0.5477 - val_categorical_accuracy: 0.8017 - 475ms/epoch - 24ms/step
Epoch 346/1500
20/20 - 0s - loss: 0.5440 - categorical_accuracy: 0.8015 - val_loss: 0.5479 - val_categorical_accuracy: 0.8011 - 460ms/epoch - 23ms/step
Epoch 347/1500
20/20 - 0s - loss: 0.5483 - categorical_accuracy: 0.7991 - val_loss: 0.5634 - val_categorical_accuracy: 0.7928 - 476ms/epoch - 24ms/step
Epoch 348/1500
20/20 - 0s - loss: 0.5614 - categorical_accuracy: 0.7929 - val_loss: 0.5712 - val_categorical_accuracy: 0.7918 - 474ms/epoch - 24ms/step
Epoch 349/1500
20/20 - 0s - loss: 0.5511 - categorical_accuracy: 0.7972 - val_loss: 0.5533 - val_categorical_accuracy: 0.7954 - 478ms/epoch - 24ms/step
Epoch 350/1500
20/20 - 1s - loss: 0.5540 - categorical_accuracy: 0.7953 - val_loss: 0.5659 - val_categorical_accuracy: 0.7919 - 719ms/epoch - 36ms/step
Epoch 351/1500
20/20 - 0s - loss: 0.5609 - categorical_accuracy: 0.7926 - val_loss: 0.5681 - val_categorical_accuracy: 0.7891 - 473ms/epoch - 24ms/step
Epoch 352/1500
20/20 - 0s - loss: 0.5488 - categorical_accuracy: 0.7979 - val_loss: 0.5469 - val_categorical_accuracy: 0.8026 - 456ms/epoch - 23ms/step
Epoch 353/1500
20/20 - 0s - loss: 0.7646 - categorical_accuracy: 0.7476 - val_loss: 0.5866 - val_categorical_accuracy: 0.7880 - 484ms/epoch - 24ms/step
Epoch 354/1500
20/20 - 0s - loss: 0.5361 - categorical_accuracy: 0.8052 - val_loss: 0.5390 - val_categorical_accuracy: 0.8054 - 477ms/epoch - 24ms/step
Epoch 355/1500
20/20 - 1s - loss: 0.5291 - categorical_accuracy: 0.8078 - val_loss: 0.5358 - val_categorical_accuracy: 0.8051 - 505ms/epoch - 25ms/step
Epoch 356/1500
20/20 - 1s - loss: 0.5263 - categorical_accuracy: 0.8087 - val_loss: 0.5341 - val_categorical_accuracy: 0.8073 - 509ms/epoch - 25ms/step
Epoch 357/1500
20/20 - 0s - loss: 0.5594 - categorical_accuracy: 0.7938 - val_loss: 0.6113 - val_categorical_accuracy: 0.7712 - 491ms/epoch - 25ms/step
Epoch 358/1500
20/20 - 0s - loss: 0.5617 - categorical_accuracy: 0.7927 - val_loss: 0.5455 - val_categorical_accuracy: 0.8017 - 478ms/epoch - 24ms/step
Epoch 359/1500
20/20 - 0s - loss: 0.5431 - categorical_accuracy: 0.7998 - val_loss: 0.5527 - val_categorical_accuracy: 0.7965 - 473ms/epoch - 24ms/step
Epoch 360/1500
20/20 - 0s - loss: 0.5407 - categorical_accuracy: 0.8017 - val_loss: 0.5506 - val_categorical_accuracy: 0.7988 - 473ms/epoch - 24ms/step
Epoch 361/1500
20/20 - 0s - loss: 0.5456 - categorical_accuracy: 0.7994 - val_loss: 0.5623 - val_categorical_accuracy: 0.7941 - 485ms/epoch - 24ms/step
Epoch 362/1500
20/20 - 0s - loss: 0.5486 - categorical_accuracy: 0.7981 - val_loss: 0.5558 - val_categorical_accuracy: 0.7956 - 462ms/epoch - 23ms/step
Epoch 363/1500
20/20 - 0s - loss: 0.5381 - categorical_accuracy: 0.8022 - val_loss: 0.5452 - val_categorical_accuracy: 0.7993 - 469ms/epoch - 23ms/step
Epoch 364/1500
20/20 - 0s - loss: 0.5471 - categorical_accuracy: 0.7975 - val_loss: 0.5772 - val_categorical_accuracy: 0.7902 - 458ms/epoch - 23ms/step
Epoch 365/1500
20/20 - 0s - loss: 0.7162 - categorical_accuracy: 0.7476 - val_loss: 0.5318 - val_categorical_accuracy: 0.8059 - 456ms/epoch - 23ms/step
Epoch 366/1500
20/20 - 0s - loss: 0.5207 - categorical_accuracy: 0.8113 - val_loss: 0.5263 - val_categorical_accuracy: 0.8089 - 466ms/epoch - 23ms/step
Epoch 367/1500
20/20 - 0s - loss: 0.5179 - categorical_accuracy: 0.8122 - val_loss: 0.5287 - val_categorical_accuracy: 0.8043 - 461ms/epoch - 23ms/step
Epoch 368/1500
20/20 - 0s - loss: 0.5371 - categorical_accuracy: 0.8024 - val_loss: 0.5341 - val_categorical_accuracy: 0.8029 - 466ms/epoch - 23ms/step
Epoch 369/1500
20/20 - 0s - loss: 0.5346 - categorical_accuracy: 0.8037 - val_loss: 0.5441 - val_categorical_accuracy: 0.7974 - 474ms/epoch - 24ms/step
Epoch 370/1500
20/20 - 0s - loss: 0.5531 - categorical_accuracy: 0.7964 - val_loss: 0.5491 - val_categorical_accuracy: 0.7955 - 478ms/epoch - 24ms/step
Epoch 371/1500
20/20 - 0s - loss: 0.5353 - categorical_accuracy: 0.8035 - val_loss: 0.5522 - val_categorical_accuracy: 0.7942 - 446ms/epoch - 22ms/step
Epoch 372/1500
20/20 - 0s - loss: 0.5369 - categorical_accuracy: 0.8036 - val_loss: 0.5271 - val_categorical_accuracy: 0.8041 - 467ms/epoch - 23ms/step
Epoch 373/1500
20/20 - 0s - loss: 0.5191 - categorical_accuracy: 0.8108 - val_loss: 0.5252 - val_categorical_accuracy: 0.8067 - 458ms/epoch - 23ms/step
Epoch 374/1500
20/20 - 0s - loss: 0.5293 - categorical_accuracy: 0.8058 - val_loss: 0.5466 - val_categorical_accuracy: 0.7969 - 481ms/epoch - 24ms/step
Epoch 375/1500
20/20 - 0s - loss: 0.5536 - categorical_accuracy: 0.7957 - val_loss: 0.5322 - val_categorical_accuracy: 0.8053 - 452ms/epoch - 23ms/step
Epoch 376/1500
20/20 - 0s - loss: 0.5114 - categorical_accuracy: 0.8154 - val_loss: 0.5160 - val_categorical_accuracy: 0.8151 - 474ms/epoch - 24ms/step
Epoch 377/1500
20/20 - 0s - loss: 0.6164 - categorical_accuracy: 0.7863 - val_loss: 1.1044 - val_categorical_accuracy: 0.6359 - 465ms/epoch - 23ms/step
Epoch 378/1500
20/20 - 0s - loss: 0.6590 - categorical_accuracy: 0.7721 - val_loss: 0.5207 - val_categorical_accuracy: 0.8123 - 474ms/epoch - 24ms/step
Epoch 379/1500
20/20 - 0s - loss: 0.5100 - categorical_accuracy: 0.8158 - val_loss: 0.5168 - val_categorical_accuracy: 0.8145 - 467ms/epoch - 23ms/step
Epoch 380/1500
20/20 - 0s - loss: 0.5081 - categorical_accuracy: 0.8162 - val_loss: 0.5227 - val_categorical_accuracy: 0.8116 - 472ms/epoch - 24ms/step
Epoch 381/1500
20/20 - 0s - loss: 0.5272 - categorical_accuracy: 0.8070 - val_loss: 0.5544 - val_categorical_accuracy: 0.7974 - 460ms/epoch - 23ms/step
Epoch 382/1500
20/20 - 0s - loss: 0.5450 - categorical_accuracy: 0.7993 - val_loss: 0.5723 - val_categorical_accuracy: 0.7880 - 473ms/epoch - 24ms/step
Epoch 383/1500
20/20 - 0s - loss: 0.5305 - categorical_accuracy: 0.8054 - val_loss: 0.5209 - val_categorical_accuracy: 0.8112 - 456ms/epoch - 23ms/step
Epoch 384/1500
20/20 - 0s - loss: 0.5032 - categorical_accuracy: 0.8182 - val_loss: 0.5091 - val_categorical_accuracy: 0.8137 - 458ms/epoch - 23ms/step
Epoch 385/1500
20/20 - 0s - loss: 0.5154 - categorical_accuracy: 0.8130 - val_loss: 0.5441 - val_categorical_accuracy: 0.7966 - 466ms/epoch - 23ms/step
Epoch 386/1500
20/20 - 0s - loss: 0.5348 - categorical_accuracy: 0.8030 - val_loss: 0.5345 - val_categorical_accuracy: 0.8013 - 449ms/epoch - 22ms/step
Epoch 387/1500
20/20 - 0s - loss: 0.5258 - categorical_accuracy: 0.8083 - val_loss: 0.5545 - val_categorical_accuracy: 0.7946 - 480ms/epoch - 24ms/step
Epoch 388/1500
20/20 - 0s - loss: 0.5284 - categorical_accuracy: 0.8066 - val_loss: 0.5191 - val_categorical_accuracy: 0.8084 - 463ms/epoch - 23ms/step
Epoch 389/1500
20/20 - 0s - loss: 0.5046 - categorical_accuracy: 0.8176 - val_loss: 0.5202 - val_categorical_accuracy: 0.8085 - 470ms/epoch - 24ms/step
Epoch 390/1500
20/20 - 0s - loss: 0.6141 - categorical_accuracy: 0.7872 - val_loss: 0.6177 - val_categorical_accuracy: 0.7769 - 461ms/epoch - 23ms/step
Epoch 391/1500
20/20 - 0s - loss: 0.5168 - categorical_accuracy: 0.8139 - val_loss: 0.5033 - val_categorical_accuracy: 0.8180 - 475ms/epoch - 24ms/step
Epoch 392/1500
20/20 - 0s - loss: 0.5027 - categorical_accuracy: 0.8178 - val_loss: 0.5282 - val_categorical_accuracy: 0.8052 - 461ms/epoch - 23ms/step
Epoch 393/1500
20/20 - 0s - loss: 0.5447 - categorical_accuracy: 0.7996 - val_loss: 0.5264 - val_categorical_accuracy: 0.8055 - 483ms/epoch - 24ms/step
Epoch 394/1500
20/20 - 0s - loss: 0.4994 - categorical_accuracy: 0.8199 - val_loss: 0.4994 - val_categorical_accuracy: 0.8192 - 467ms/epoch - 23ms/step
Epoch 395/1500
20/20 - 0s - loss: 0.4928 - categorical_accuracy: 0.8224 - val_loss: 0.5176 - val_categorical_accuracy: 0.8103 - 460ms/epoch - 23ms/step
Epoch 396/1500
20/20 - 0s - loss: 0.5367 - categorical_accuracy: 0.8021 - val_loss: 0.5490 - val_categorical_accuracy: 0.7960 - 462ms/epoch - 23ms/step
Epoch 397/1500
20/20 - 0s - loss: 0.5240 - categorical_accuracy: 0.8101 - val_loss: 0.5126 - val_categorical_accuracy: 0.8128 - 491ms/epoch - 25ms/step
Epoch 398/1500
20/20 - 1s - loss: 0.5014 - categorical_accuracy: 0.8172 - val_loss: 0.5103 - val_categorical_accuracy: 0.8115 - 513ms/epoch - 26ms/step
Epoch 399/1500
20/20 - 1s - loss: 0.5302 - categorical_accuracy: 0.8054 - val_loss: 0.5248 - val_categorical_accuracy: 0.8075 - 504ms/epoch - 25ms/step
Epoch 400/1500
20/20 - 1s - loss: 0.5013 - categorical_accuracy: 0.8181 - val_loss: 0.5079 - val_categorical_accuracy: 0.8150 - 500ms/epoch - 25ms/step
Epoch 401/1500
20/20 - 0s - loss: 0.5031 - categorical_accuracy: 0.8177 - val_loss: 0.5151 - val_categorical_accuracy: 0.8096 - 497ms/epoch - 25ms/step
Epoch 402/1500
20/20 - 0s - loss: 0.5109 - categorical_accuracy: 0.8144 - val_loss: 0.4939 - val_categorical_accuracy: 0.8201 - 498ms/epoch - 25ms/step
Epoch 403/1500
20/20 - 0s - loss: 0.4857 - categorical_accuracy: 0.8255 - val_loss: 0.5114 - val_categorical_accuracy: 0.8126 - 484ms/epoch - 24ms/step
Epoch 404/1500
20/20 - 0s - loss: 0.8127 - categorical_accuracy: 0.7389 - val_loss: 0.6456 - val_categorical_accuracy: 0.7710 - 497ms/epoch - 25ms/step
Epoch 405/1500
20/20 - 1s - loss: 0.5078 - categorical_accuracy: 0.8184 - val_loss: 0.5006 - val_categorical_accuracy: 0.8189 - 513ms/epoch - 26ms/step
Epoch 406/1500
20/20 - 0s - loss: 0.4879 - categorical_accuracy: 0.8256 - val_loss: 0.4950 - val_categorical_accuracy: 0.8220 - 499ms/epoch - 25ms/step
Epoch 407/1500
20/20 - 1s - loss: 0.4858 - categorical_accuracy: 0.8259 - val_loss: 0.5012 - val_categorical_accuracy: 0.8224 - 514ms/epoch - 26ms/step
Epoch 408/1500
20/20 - 0s - loss: 0.4953 - categorical_accuracy: 0.8211 - val_loss: 0.5427 - val_categorical_accuracy: 0.8047 - 499ms/epoch - 25ms/step
Epoch 409/1500
20/20 - 1s - loss: 0.5367 - categorical_accuracy: 0.8027 - val_loss: 0.5011 - val_categorical_accuracy: 0.8233 - 512ms/epoch - 26ms/step
Epoch 410/1500
20/20 - 1s - loss: 0.4854 - categorical_accuracy: 0.8259 - val_loss: 0.4952 - val_categorical_accuracy: 0.8249 - 505ms/epoch - 25ms/step
Epoch 411/1500
20/20 - 1s - loss: 0.4899 - categorical_accuracy: 0.8230 - val_loss: 0.5408 - val_categorical_accuracy: 0.8026 - 504ms/epoch - 25ms/step
Epoch 412/1500
20/20 - 0s - loss: 0.5186 - categorical_accuracy: 0.8109 - val_loss: 0.5210 - val_categorical_accuracy: 0.8095 - 493ms/epoch - 25ms/step
Epoch 413/1500
20/20 - 1s - loss: 0.5104 - categorical_accuracy: 0.8142 - val_loss: 0.5148 - val_categorical_accuracy: 0.8149 - 532ms/epoch - 27ms/step
Epoch 414/1500
20/20 - 0s - loss: 0.5044 - categorical_accuracy: 0.8172 - val_loss: 0.5004 - val_categorical_accuracy: 0.8203 - 497ms/epoch - 25ms/step
Epoch 415/1500
20/20 - 1s - loss: 0.4767 - categorical_accuracy: 0.8293 - val_loss: 0.4874 - val_categorical_accuracy: 0.8224 - 515ms/epoch - 26ms/step
Epoch 416/1500
20/20 - 1s - loss: 0.4822 - categorical_accuracy: 0.8270 - val_loss: 0.5044 - val_categorical_accuracy: 0.8150 - 505ms/epoch - 25ms/step
Epoch 417/1500
20/20 - 1s - loss: 0.5376 - categorical_accuracy: 0.8024 - val_loss: 0.5299 - val_categorical_accuracy: 0.8035 - 528ms/epoch - 26ms/step
Epoch 418/1500
20/20 - 0s - loss: 0.4975 - categorical_accuracy: 0.8208 - val_loss: 0.4928 - val_categorical_accuracy: 0.8197 - 499ms/epoch - 25ms/step
Epoch 419/1500
20/20 - 1s - loss: 0.4817 - categorical_accuracy: 0.8259 - val_loss: 0.4837 - val_categorical_accuracy: 0.8231 - 534ms/epoch - 27ms/step
Epoch 420/1500
20/20 - 0s - loss: 0.4758 - categorical_accuracy: 0.8296 - val_loss: 0.4959 - val_categorical_accuracy: 0.8182 - 496ms/epoch - 25ms/step
Epoch 421/1500
20/20 - 1s - loss: 0.5066 - categorical_accuracy: 0.8159 - val_loss: 0.5472 - val_categorical_accuracy: 0.7956 - 507ms/epoch - 25ms/step
Epoch 422/1500
20/20 - 1s - loss: 0.5072 - categorical_accuracy: 0.8145 - val_loss: 0.4963 - val_categorical_accuracy: 0.8170 - 505ms/epoch - 25ms/step
Epoch 423/1500
20/20 - 1s - loss: 0.4870 - categorical_accuracy: 0.8236 - val_loss: 0.4881 - val_categorical_accuracy: 0.8226 - 528ms/epoch - 26ms/step
Epoch 424/1500
20/20 - 1s - loss: 0.4901 - categorical_accuracy: 0.8226 - val_loss: 0.5104 - val_categorical_accuracy: 0.8125 - 502ms/epoch - 25ms/step
Epoch 425/1500
20/20 - 1s - loss: 0.5114 - categorical_accuracy: 0.8129 - val_loss: 0.4972 - val_categorical_accuracy: 0.8182 - 528ms/epoch - 26ms/step
Epoch 426/1500
20/20 - 0s - loss: 0.4772 - categorical_accuracy: 0.8289 - val_loss: 0.4846 - val_categorical_accuracy: 0.8227 - 492ms/epoch - 25ms/step
Epoch 427/1500
20/20 - 1s - loss: 0.6048 - categorical_accuracy: 0.7990 - val_loss: 0.6472 - val_categorical_accuracy: 0.7672 - 526ms/epoch - 26ms/step
Epoch 428/1500
20/20 - 1s - loss: 0.9633 - categorical_accuracy: 0.7294 - val_loss: 0.5049 - val_categorical_accuracy: 0.8210 - 513ms/epoch - 26ms/step
Epoch 429/1500
20/20 - 0s - loss: 0.4870 - categorical_accuracy: 0.8285 - val_loss: 0.4902 - val_categorical_accuracy: 0.8247 - 482ms/epoch - 24ms/step
Epoch 430/1500
20/20 - 0s - loss: 0.4760 - categorical_accuracy: 0.8310 - val_loss: 0.4836 - val_categorical_accuracy: 0.8273 - 474ms/epoch - 24ms/step
Epoch 431/1500
20/20 - 0s - loss: 0.4697 - categorical_accuracy: 0.8335 - val_loss: 0.4766 - val_categorical_accuracy: 0.8296 - 497ms/epoch - 25ms/step
Epoch 432/1500
20/20 - 0s - loss: 0.4667 - categorical_accuracy: 0.8340 - val_loss: 0.4771 - val_categorical_accuracy: 0.8286 - 459ms/epoch - 23ms/step
Epoch 433/1500
20/20 - 0s - loss: 0.4640 - categorical_accuracy: 0.8347 - val_loss: 0.4732 - val_categorical_accuracy: 0.8299 - 462ms/epoch - 23ms/step
Epoch 434/1500
20/20 - 0s - loss: 0.4620 - categorical_accuracy: 0.8355 - val_loss: 0.4775 - val_categorical_accuracy: 0.8287 - 448ms/epoch - 22ms/step
Epoch 435/1500
20/20 - 0s - loss: 0.4716 - categorical_accuracy: 0.8303 - val_loss: 0.5344 - val_categorical_accuracy: 0.8010 - 474ms/epoch - 24ms/step
Epoch 436/1500
20/20 - 0s - loss: 0.5156 - categorical_accuracy: 0.8114 - val_loss: 0.5189 - val_categorical_accuracy: 0.8136 - 459ms/epoch - 23ms/step
Epoch 437/1500
20/20 - 0s - loss: 0.4842 - categorical_accuracy: 0.8258 - val_loss: 0.4836 - val_categorical_accuracy: 0.8266 - 485ms/epoch - 24ms/step
Epoch 438/1500
20/20 - 1s - loss: 0.4768 - categorical_accuracy: 0.8264 - val_loss: 0.4779 - val_categorical_accuracy: 0.8318 - 524ms/epoch - 26ms/step
Epoch 439/1500
20/20 - 0s - loss: 0.4831 - categorical_accuracy: 0.8250 - val_loss: 0.4954 - val_categorical_accuracy: 0.8205 - 466ms/epoch - 23ms/step
Epoch 440/1500
20/20 - 0s - loss: 0.4886 - categorical_accuracy: 0.8220 - val_loss: 0.4998 - val_categorical_accuracy: 0.8171 - 468ms/epoch - 23ms/step
Epoch 441/1500
20/20 - 0s - loss: 0.4848 - categorical_accuracy: 0.8239 - val_loss: 0.4711 - val_categorical_accuracy: 0.8336 - 465ms/epoch - 23ms/step
Epoch 442/1500
20/20 - 0s - loss: 0.4699 - categorical_accuracy: 0.8299 - val_loss: 0.4750 - val_categorical_accuracy: 0.8319 - 483ms/epoch - 24ms/step
Epoch 443/1500
20/20 - 0s - loss: 0.4719 - categorical_accuracy: 0.8310 - val_loss: 0.4882 - val_categorical_accuracy: 0.8266 - 470ms/epoch - 24ms/step
Epoch 444/1500
20/20 - 0s - loss: 0.5016 - categorical_accuracy: 0.8169 - val_loss: 0.5016 - val_categorical_accuracy: 0.8185 - 459ms/epoch - 23ms/step
Epoch 445/1500
20/20 - 0s - loss: 0.4799 - categorical_accuracy: 0.8275 - val_loss: 0.4904 - val_categorical_accuracy: 0.8239 - 472ms/epoch - 24ms/step
Epoch 446/1500
20/20 - 1s - loss: 0.5966 - categorical_accuracy: 0.8008 - val_loss: 0.7736 - val_categorical_accuracy: 0.7403 - 500ms/epoch - 25ms/step
Epoch 447/1500
20/20 - 1s - loss: 0.6037 - categorical_accuracy: 0.7979 - val_loss: 0.4676 - val_categorical_accuracy: 0.8334 - 512ms/epoch - 26ms/step
Epoch 448/1500
20/20 - 0s - loss: 0.4545 - categorical_accuracy: 0.8385 - val_loss: 0.4628 - val_categorical_accuracy: 0.8356 - 464ms/epoch - 23ms/step
Epoch 449/1500
20/20 - 0s - loss: 0.4512 - categorical_accuracy: 0.8397 - val_loss: 0.4618 - val_categorical_accuracy: 0.8353 - 469ms/epoch - 23ms/step
Epoch 450/1500
20/20 - 0s - loss: 0.4565 - categorical_accuracy: 0.8343 - val_loss: 0.4687 - val_categorical_accuracy: 0.8294 - 469ms/epoch - 23ms/step
Epoch 451/1500
20/20 - 0s - loss: 0.4689 - categorical_accuracy: 0.8253 - val_loss: 0.4805 - val_categorical_accuracy: 0.8228 - 455ms/epoch - 23ms/step
Epoch 452/1500
20/20 - 0s - loss: 0.4728 - categorical_accuracy: 0.8258 - val_loss: 0.4952 - val_categorical_accuracy: 0.8217 - 463ms/epoch - 23ms/step
Epoch 453/1500
20/20 - 0s - loss: 0.4855 - categorical_accuracy: 0.8246 - val_loss: 0.5290 - val_categorical_accuracy: 0.8070 - 450ms/epoch - 23ms/step
Epoch 454/1500
20/20 - 0s - loss: 0.4979 - categorical_accuracy: 0.8184 - val_loss: 0.4833 - val_categorical_accuracy: 0.8266 - 464ms/epoch - 23ms/step
Epoch 455/1500
20/20 - 0s - loss: 0.4652 - categorical_accuracy: 0.8337 - val_loss: 0.4620 - val_categorical_accuracy: 0.8355 - 458ms/epoch - 23ms/step
Epoch 456/1500
20/20 - 0s - loss: 0.4518 - categorical_accuracy: 0.8388 - val_loss: 0.4696 - val_categorical_accuracy: 0.8345 - 457ms/epoch - 23ms/step
Epoch 457/1500
20/20 - 0s - loss: 0.4775 - categorical_accuracy: 0.8233 - val_loss: 0.5039 - val_categorical_accuracy: 0.8103 - 465ms/epoch - 23ms/step
Epoch 458/1500
20/20 - 0s - loss: 0.4694 - categorical_accuracy: 0.8257 - val_loss: 0.4635 - val_categorical_accuracy: 0.8312 - 464ms/epoch - 23ms/step
Epoch 459/1500
20/20 - 0s - loss: 0.4530 - categorical_accuracy: 0.8349 - val_loss: 0.5055 - val_categorical_accuracy: 0.8073 - 458ms/epoch - 23ms/step
Epoch 460/1500
20/20 - 0s - loss: 0.4925 - categorical_accuracy: 0.8171 - val_loss: 0.4935 - val_categorical_accuracy: 0.8183 - 458ms/epoch - 23ms/step
Epoch 461/1500
20/20 - 0s - loss: 0.4716 - categorical_accuracy: 0.8303 - val_loss: 0.4735 - val_categorical_accuracy: 0.8279 - 457ms/epoch - 23ms/step
Epoch 462/1500
20/20 - 0s - loss: 0.4887 - categorical_accuracy: 0.8240 - val_loss: 0.4833 - val_categorical_accuracy: 0.8228 - 455ms/epoch - 23ms/step
Epoch 463/1500
20/20 - 0s - loss: 0.4734 - categorical_accuracy: 0.8262 - val_loss: 0.4809 - val_categorical_accuracy: 0.8198 - 453ms/epoch - 23ms/step
Epoch 464/1500
20/20 - 0s - loss: 0.4578 - categorical_accuracy: 0.8307 - val_loss: 0.4669 - val_categorical_accuracy: 0.8269 - 473ms/epoch - 24ms/step
Epoch 465/1500
20/20 - 0s - loss: 0.4578 - categorical_accuracy: 0.8306 - val_loss: 0.4528 - val_categorical_accuracy: 0.8380 - 470ms/epoch - 24ms/step
Epoch 466/1500
20/20 - 0s - loss: 0.4538 - categorical_accuracy: 0.8357 - val_loss: 0.4971 - val_categorical_accuracy: 0.8125 - 459ms/epoch - 23ms/step
Epoch 467/1500
20/20 - 0s - loss: 0.4903 - categorical_accuracy: 0.8177 - val_loss: 0.5102 - val_categorical_accuracy: 0.8158 - 470ms/epoch - 24ms/step
Epoch 468/1500
20/20 - 0s - loss: 0.4759 - categorical_accuracy: 0.8284 - val_loss: 0.4898 - val_categorical_accuracy: 0.8259 - 459ms/epoch - 23ms/step
Epoch 469/1500
20/20 - 0s - loss: 0.4613 - categorical_accuracy: 0.8347 - val_loss: 0.4730 - val_categorical_accuracy: 0.8341 - 474ms/epoch - 24ms/step
Epoch 470/1500
20/20 - 0s - loss: 0.6361 - categorical_accuracy: 0.8027 - val_loss: 1.0968 - val_categorical_accuracy: 0.6856 - 462ms/epoch - 23ms/step
Epoch 471/1500
20/20 - 0s - loss: 0.5997 - categorical_accuracy: 0.8069 - val_loss: 0.4540 - val_categorical_accuracy: 0.8394 - 470ms/epoch - 24ms/step
Epoch 472/1500
20/20 - 0s - loss: 0.4399 - categorical_accuracy: 0.8443 - val_loss: 0.4532 - val_categorical_accuracy: 0.8369 - 460ms/epoch - 23ms/step
Epoch 473/1500
20/20 - 0s - loss: 0.4358 - categorical_accuracy: 0.8459 - val_loss: 0.4445 - val_categorical_accuracy: 0.8425 - 473ms/epoch - 24ms/step
Epoch 474/1500
20/20 - 0s - loss: 0.4377 - categorical_accuracy: 0.8449 - val_loss: 0.4757 - val_categorical_accuracy: 0.8242 - 474ms/epoch - 24ms/step
Epoch 475/1500
20/20 - 0s - loss: 0.4664 - categorical_accuracy: 0.8285 - val_loss: 0.4648 - val_categorical_accuracy: 0.8293 - 452ms/epoch - 23ms/step
Epoch 476/1500
20/20 - 0s - loss: 0.4551 - categorical_accuracy: 0.8326 - val_loss: 0.4608 - val_categorical_accuracy: 0.8298 - 473ms/epoch - 24ms/step
Epoch 477/1500
20/20 - 0s - loss: 0.4611 - categorical_accuracy: 0.8274 - val_loss: 0.4898 - val_categorical_accuracy: 0.8130 - 472ms/epoch - 24ms/step
Epoch 478/1500
20/20 - 0s - loss: 0.4580 - categorical_accuracy: 0.8310 - val_loss: 0.4533 - val_categorical_accuracy: 0.8404 - 474ms/epoch - 24ms/step
Epoch 479/1500
20/20 - 0s - loss: 0.4595 - categorical_accuracy: 0.8334 - val_loss: 0.4914 - val_categorical_accuracy: 0.8240 - 458ms/epoch - 23ms/step
Epoch 480/1500
20/20 - 0s - loss: 0.5050 - categorical_accuracy: 0.8178 - val_loss: 0.4868 - val_categorical_accuracy: 0.8273 - 473ms/epoch - 24ms/step
Epoch 481/1500
20/20 - 0s - loss: 0.4438 - categorical_accuracy: 0.8429 - val_loss: 0.4456 - val_categorical_accuracy: 0.8415 - 457ms/epoch - 23ms/step
Epoch 482/1500
20/20 - 0s - loss: 0.4385 - categorical_accuracy: 0.8407 - val_loss: 0.4675 - val_categorical_accuracy: 0.8243 - 473ms/epoch - 24ms/step
Epoch 483/1500
20/20 - 0s - loss: 0.4604 - categorical_accuracy: 0.8270 - val_loss: 0.4528 - val_categorical_accuracy: 0.8338 - 456ms/epoch - 23ms/step
Epoch 484/1500
20/20 - 0s - loss: 0.4555 - categorical_accuracy: 0.8293 - val_loss: 0.4676 - val_categorical_accuracy: 0.8241 - 469ms/epoch - 23ms/step
Epoch 485/1500
20/20 - 0s - loss: 0.4505 - categorical_accuracy: 0.8321 - val_loss: 0.4529 - val_categorical_accuracy: 0.8341 - 460ms/epoch - 23ms/step
Epoch 486/1500
20/20 - 0s - loss: 0.4496 - categorical_accuracy: 0.8363 - val_loss: 0.5108 - val_categorical_accuracy: 0.8125 - 471ms/epoch - 24ms/step
Epoch 487/1500
20/20 - 0s - loss: 0.5021 - categorical_accuracy: 0.8182 - val_loss: 0.4511 - val_categorical_accuracy: 0.8357 - 458ms/epoch - 23ms/step
Epoch 488/1500
20/20 - 0s - loss: 0.4308 - categorical_accuracy: 0.8474 - val_loss: 0.4432 - val_categorical_accuracy: 0.8393 - 477ms/epoch - 24ms/step
Epoch 489/1500
20/20 - 0s - loss: 0.4368 - categorical_accuracy: 0.8396 - val_loss: 0.4697 - val_categorical_accuracy: 0.8237 - 458ms/epoch - 23ms/step
Epoch 490/1500
20/20 - 0s - loss: 0.4555 - categorical_accuracy: 0.8285 - val_loss: 0.4599 - val_categorical_accuracy: 0.8288 - 468ms/epoch - 23ms/step
Epoch 491/1500
20/20 - 0s - loss: 0.4422 - categorical_accuracy: 0.8385 - val_loss: 0.4794 - val_categorical_accuracy: 0.8229 - 464ms/epoch - 23ms/step
Epoch 492/1500
20/20 - 0s - loss: 0.7518 - categorical_accuracy: 0.7754 - val_loss: 0.5068 - val_categorical_accuracy: 0.8181 - 460ms/epoch - 23ms/step
Epoch 493/1500
20/20 - 0s - loss: 0.4366 - categorical_accuracy: 0.8456 - val_loss: 0.4398 - val_categorical_accuracy: 0.8440 - 473ms/epoch - 24ms/step
Epoch 494/1500
20/20 - 0s - loss: 0.4240 - categorical_accuracy: 0.8505 - val_loss: 0.4350 - val_categorical_accuracy: 0.8448 - 468ms/epoch - 23ms/step
Epoch 495/1500
20/20 - 0s - loss: 0.4283 - categorical_accuracy: 0.8463 - val_loss: 0.4691 - val_categorical_accuracy: 0.8233 - 466ms/epoch - 23ms/step
Epoch 496/1500
20/20 - 0s - loss: 0.4529 - categorical_accuracy: 0.8316 - val_loss: 0.4578 - val_categorical_accuracy: 0.8311 - 460ms/epoch - 23ms/step
Epoch 497/1500
20/20 - 0s - loss: 0.4368 - categorical_accuracy: 0.8398 - val_loss: 0.4661 - val_categorical_accuracy: 0.8283 - 466ms/epoch - 23ms/step
Epoch 498/1500
20/20 - 0s - loss: 0.4924 - categorical_accuracy: 0.8209 - val_loss: 0.4860 - val_categorical_accuracy: 0.8247 - 461ms/epoch - 23ms/step
Epoch 499/1500
20/20 - 0s - loss: 0.4339 - categorical_accuracy: 0.8446 - val_loss: 0.4539 - val_categorical_accuracy: 0.8362 - 485ms/epoch - 24ms/step
Epoch 500/1500
20/20 - 0s - loss: 0.4428 - categorical_accuracy: 0.8393 - val_loss: 0.4457 - val_categorical_accuracy: 0.8403 - 452ms/epoch - 23ms/step
Epoch 501/1500
20/20 - 0s - loss: 0.4311 - categorical_accuracy: 0.8425 - val_loss: 0.4464 - val_categorical_accuracy: 0.8347 - 470ms/epoch - 24ms/step
Epoch 502/1500
20/20 - 0s - loss: 0.4509 - categorical_accuracy: 0.8349 - val_loss: 0.4721 - val_categorical_accuracy: 0.8284 - 458ms/epoch - 23ms/step
Epoch 503/1500
20/20 - 0s - loss: 0.4564 - categorical_accuracy: 0.8354 - val_loss: 0.4595 - val_categorical_accuracy: 0.8303 - 472ms/epoch - 24ms/step
Epoch 504/1500
20/20 - 0s - loss: 0.4477 - categorical_accuracy: 0.8345 - val_loss: 0.4537 - val_categorical_accuracy: 0.8312 - 469ms/epoch - 23ms/step
Epoch 505/1500
20/20 - 0s - loss: 0.4307 - categorical_accuracy: 0.8420 - val_loss: 0.4403 - val_categorical_accuracy: 0.8400 - 468ms/epoch - 23ms/step
Epoch 506/1500
20/20 - 0s - loss: 0.4500 - categorical_accuracy: 0.8326 - val_loss: 0.4859 - val_categorical_accuracy: 0.8200 - 461ms/epoch - 23ms/step
Epoch 507/1500
20/20 - 0s - loss: 0.4588 - categorical_accuracy: 0.8325 - val_loss: 0.4903 - val_categorical_accuracy: 0.8212 - 454ms/epoch - 23ms/step
Epoch 508/1500
20/20 - 0s - loss: 0.4632 - categorical_accuracy: 0.8339 - val_loss: 0.4447 - val_categorical_accuracy: 0.8446 - 460ms/epoch - 23ms/step
Epoch 509/1500
20/20 - 0s - loss: 0.4256 - categorical_accuracy: 0.8491 - val_loss: 0.4341 - val_categorical_accuracy: 0.8446 - 453ms/epoch - 23ms/step
Epoch 510/1500
20/20 - 0s - loss: 0.4375 - categorical_accuracy: 0.8375 - val_loss: 0.4452 - val_categorical_accuracy: 0.8367 - 454ms/epoch - 23ms/step
Epoch 511/1500
20/20 - 0s - loss: 0.4333 - categorical_accuracy: 0.8381 - val_loss: 0.4525 - val_categorical_accuracy: 0.8327 - 458ms/epoch - 23ms/step
Epoch 512/1500
20/20 - 1s - loss: 0.4455 - categorical_accuracy: 0.8341 - val_loss: 0.4368 - val_categorical_accuracy: 0.8433 - 524ms/epoch - 26ms/step
Epoch 513/1500
20/20 - 1s - loss: 0.4388 - categorical_accuracy: 0.8428 - val_loss: 0.4714 - val_categorical_accuracy: 0.8330 - 507ms/epoch - 25ms/step
Epoch 514/1500
20/20 - 1s - loss: 0.4734 - categorical_accuracy: 0.8303 - val_loss: 0.4798 - val_categorical_accuracy: 0.8292 - 526ms/epoch - 26ms/step
Epoch 515/1500
20/20 - 1s - loss: 0.4424 - categorical_accuracy: 0.8403 - val_loss: 0.4600 - val_categorical_accuracy: 0.8302 - 522ms/epoch - 26ms/step
Epoch 516/1500
20/20 - 1s - loss: 0.4391 - categorical_accuracy: 0.8355 - val_loss: 0.4534 - val_categorical_accuracy: 0.8302 - 528ms/epoch - 26ms/step
Epoch 517/1500
20/20 - 1s - loss: 0.4341 - categorical_accuracy: 0.8373 - val_loss: 0.4410 - val_categorical_accuracy: 0.8392 - 518ms/epoch - 26ms/step
Epoch 518/1500
20/20 - 1s - loss: 0.7469 - categorical_accuracy: 0.7764 - val_loss: 0.4391 - val_categorical_accuracy: 0.8428 - 553ms/epoch - 28ms/step
Epoch 519/1500
20/20 - 1s - loss: 0.4163 - categorical_accuracy: 0.8535 - val_loss: 0.4250 - val_categorical_accuracy: 0.8486 - 530ms/epoch - 27ms/step
Epoch 520/1500
20/20 - 1s - loss: 0.4096 - categorical_accuracy: 0.8552 - val_loss: 0.4264 - val_categorical_accuracy: 0.8467 - 510ms/epoch - 26ms/step
Epoch 521/1500
20/20 - 1s - loss: 0.4186 - categorical_accuracy: 0.8485 - val_loss: 0.4269 - val_categorical_accuracy: 0.8506 - 514ms/epoch - 26ms/step
Epoch 522/1500
20/20 - 1s - loss: 0.4172 - categorical_accuracy: 0.8503 - val_loss: 0.4312 - val_categorical_accuracy: 0.8456 - 514ms/epoch - 26ms/step
Epoch 523/1500
20/20 - 1s - loss: 0.4321 - categorical_accuracy: 0.8422 - val_loss: 0.4563 - val_categorical_accuracy: 0.8314 - 512ms/epoch - 26ms/step
Epoch 524/1500
20/20 - 1s - loss: 0.4257 - categorical_accuracy: 0.8443 - val_loss: 0.4182 - val_categorical_accuracy: 0.8511 - 526ms/epoch - 26ms/step
Epoch 525/1500
20/20 - 1s - loss: 0.4443 - categorical_accuracy: 0.8339 - val_loss: 0.4923 - val_categorical_accuracy: 0.8179 - 523ms/epoch - 26ms/step
Epoch 526/1500
20/20 - 1s - loss: 0.4770 - categorical_accuracy: 0.8279 - val_loss: 0.4268 - val_categorical_accuracy: 0.8466 - 502ms/epoch - 25ms/step
Epoch 527/1500
20/20 - 1s - loss: 0.4125 - categorical_accuracy: 0.8541 - val_loss: 0.4411 - val_categorical_accuracy: 0.8408 - 528ms/epoch - 26ms/step
Epoch 528/1500
20/20 - 1s - loss: 0.4292 - categorical_accuracy: 0.8443 - val_loss: 0.4321 - val_categorical_accuracy: 0.8424 - 561ms/epoch - 28ms/step
Epoch 529/1500
20/20 - 1s - loss: 0.4213 - categorical_accuracy: 0.8454 - val_loss: 0.4387 - val_categorical_accuracy: 0.8406 - 540ms/epoch - 27ms/step
Epoch 530/1500
20/20 - 1s - loss: 0.4463 - categorical_accuracy: 0.8372 - val_loss: 0.4787 - val_categorical_accuracy: 0.8290 - 534ms/epoch - 27ms/step
Epoch 531/1500
20/20 - 1s - loss: 0.4569 - categorical_accuracy: 0.8369 - val_loss: 0.4288 - val_categorical_accuracy: 0.8507 - 525ms/epoch - 26ms/step
Epoch 532/1500
20/20 - 1s - loss: 0.4179 - categorical_accuracy: 0.8516 - val_loss: 0.4297 - val_categorical_accuracy: 0.8483 - 506ms/epoch - 25ms/step
Epoch 533/1500
20/20 - 1s - loss: 0.4285 - categorical_accuracy: 0.8418 - val_loss: 0.4307 - val_categorical_accuracy: 0.8418 - 504ms/epoch - 25ms/step
Epoch 534/1500
20/20 - 0s - loss: 0.4257 - categorical_accuracy: 0.8427 - val_loss: 0.4358 - val_categorical_accuracy: 0.8384 - 492ms/epoch - 25ms/step
Epoch 535/1500
20/20 - 1s - loss: 0.4287 - categorical_accuracy: 0.8401 - val_loss: 0.4323 - val_categorical_accuracy: 0.8419 - 507ms/epoch - 25ms/step
Epoch 536/1500
20/20 - 1s - loss: 0.4139 - categorical_accuracy: 0.8483 - val_loss: 0.4447 - val_categorical_accuracy: 0.8334 - 544ms/epoch - 27ms/step
Epoch 537/1500
20/20 - 1s - loss: 0.4442 - categorical_accuracy: 0.8361 - val_loss: 0.5949 - val_categorical_accuracy: 0.7795 - 523ms/epoch - 26ms/step
Epoch 538/1500
20/20 - 1s - loss: 0.6270 - categorical_accuracy: 0.8078 - val_loss: 0.4126 - val_categorical_accuracy: 0.8530 - 510ms/epoch - 26ms/step
Epoch 539/1500
20/20 - 1s - loss: 0.3964 - categorical_accuracy: 0.8607 - val_loss: 0.4103 - val_categorical_accuracy: 0.8533 - 537ms/epoch - 27ms/step
Epoch 540/1500
20/20 - 1s - loss: 0.3949 - categorical_accuracy: 0.8610 - val_loss: 0.4161 - val_categorical_accuracy: 0.8495 - 512ms/epoch - 26ms/step
Epoch 541/1500
20/20 - 1s - loss: 0.4252 - categorical_accuracy: 0.8415 - val_loss: 0.4298 - val_categorical_accuracy: 0.8421 - 508ms/epoch - 25ms/step
Epoch 542/1500
20/20 - 1s - loss: 0.4170 - categorical_accuracy: 0.8461 - val_loss: 0.4698 - val_categorical_accuracy: 0.8231 - 565ms/epoch - 28ms/step
Epoch 543/1500
20/20 - 1s - loss: 0.4195 - categorical_accuracy: 0.8453 - val_loss: 0.4090 - val_categorical_accuracy: 0.8552 - 542ms/epoch - 27ms/step
Epoch 544/1500
20/20 - 1s - loss: 0.4146 - categorical_accuracy: 0.8489 - val_loss: 0.4517 - val_categorical_accuracy: 0.8377 - 532ms/epoch - 27ms/step
Epoch 545/1500
20/20 - 0s - loss: 0.5108 - categorical_accuracy: 0.8154 - val_loss: 0.4467 - val_categorical_accuracy: 0.8393 - 488ms/epoch - 24ms/step
Epoch 546/1500
20/20 - 0s - loss: 0.4093 - categorical_accuracy: 0.8549 - val_loss: 0.4155 - val_categorical_accuracy: 0.8504 - 462ms/epoch - 23ms/step
Epoch 547/1500
20/20 - 0s - loss: 0.4160 - categorical_accuracy: 0.8467 - val_loss: 0.4238 - val_categorical_accuracy: 0.8444 - 473ms/epoch - 24ms/step
Epoch 548/1500
20/20 - 0s - loss: 0.4101 - categorical_accuracy: 0.8499 - val_loss: 0.4173 - val_categorical_accuracy: 0.8484 - 474ms/epoch - 24ms/step
Epoch 549/1500
20/20 - 1s - loss: 0.4045 - categorical_accuracy: 0.8545 - val_loss: 0.4237 - val_categorical_accuracy: 0.8458 - 517ms/epoch - 26ms/step
Epoch 550/1500
20/20 - 1s - loss: 0.4155 - categorical_accuracy: 0.8514 - val_loss: 0.5056 - val_categorical_accuracy: 0.8126 - 503ms/epoch - 25ms/step
Epoch 551/1500
20/20 - 0s - loss: 0.4777 - categorical_accuracy: 0.8282 - val_loss: 0.4707 - val_categorical_accuracy: 0.8285 - 488ms/epoch - 24ms/step
Epoch 552/1500
20/20 - 0s - loss: 0.4023 - categorical_accuracy: 0.8574 - val_loss: 0.4063 - val_categorical_accuracy: 0.8553 - 485ms/epoch - 24ms/step
Epoch 553/1500
20/20 - 0s - loss: 0.4189 - categorical_accuracy: 0.8461 - val_loss: 0.4818 - val_categorical_accuracy: 0.8194 - 475ms/epoch - 24ms/step
Epoch 554/1500
20/20 - 0s - loss: 0.4147 - categorical_accuracy: 0.8468 - val_loss: 0.4178 - val_categorical_accuracy: 0.8478 - 487ms/epoch - 24ms/step
Epoch 555/1500
20/20 - 0s - loss: 0.4012 - categorical_accuracy: 0.8535 - val_loss: 0.4210 - val_categorical_accuracy: 0.8467 - 487ms/epoch - 24ms/step
Epoch 556/1500
20/20 - 0s - loss: 0.4218 - categorical_accuracy: 0.8422 - val_loss: 0.4118 - val_categorical_accuracy: 0.8518 - 474ms/epoch - 24ms/step
Epoch 557/1500
20/20 - 0s - loss: 0.4077 - categorical_accuracy: 0.8505 - val_loss: 0.4126 - val_categorical_accuracy: 0.8531 - 491ms/epoch - 25ms/step
Epoch 558/1500
20/20 - 0s - loss: 0.4100 - categorical_accuracy: 0.8539 - val_loss: 0.4377 - val_categorical_accuracy: 0.8463 - 486ms/epoch - 24ms/step
Epoch 559/1500
20/20 - 0s - loss: 0.4735 - categorical_accuracy: 0.8308 - val_loss: 0.4683 - val_categorical_accuracy: 0.8349 - 490ms/epoch - 25ms/step
Epoch 560/1500
20/20 - 0s - loss: 0.4117 - categorical_accuracy: 0.8554 - val_loss: 0.4142 - val_categorical_accuracy: 0.8549 - 482ms/epoch - 24ms/step
Epoch 561/1500
20/20 - 1s - loss: 0.4300 - categorical_accuracy: 0.8386 - val_loss: 0.4144 - val_categorical_accuracy: 0.8498 - 504ms/epoch - 25ms/step
Epoch 562/1500
20/20 - 0s - loss: 0.3994 - categorical_accuracy: 0.8540 - val_loss: 0.4047 - val_categorical_accuracy: 0.8577 - 486ms/epoch - 24ms/step
Epoch 563/1500
20/20 - 0s - loss: 0.3948 - categorical_accuracy: 0.8594 - val_loss: 0.4199 - val_categorical_accuracy: 0.8497 - 498ms/epoch - 25ms/step
Epoch 564/1500
20/20 - 0s - loss: 0.4110 - categorical_accuracy: 0.8482 - val_loss: 0.4302 - val_categorical_accuracy: 0.8395 - 488ms/epoch - 24ms/step
Epoch 565/1500
20/20 - 1s - loss: 0.4036 - categorical_accuracy: 0.8521 - val_loss: 0.4050 - val_categorical_accuracy: 0.8534 - 520ms/epoch - 26ms/step
Epoch 566/1500
20/20 - 1s - loss: 0.4316 - categorical_accuracy: 0.8409 - val_loss: 0.5159 - val_categorical_accuracy: 0.8089 - 505ms/epoch - 25ms/step
Epoch 567/1500
20/20 - 1s - loss: 0.4375 - categorical_accuracy: 0.8441 - val_loss: 0.3969 - val_categorical_accuracy: 0.8585 - 524ms/epoch - 26ms/step
Epoch 568/1500
20/20 - 1s - loss: 0.3890 - categorical_accuracy: 0.8609 - val_loss: 0.4070 - val_categorical_accuracy: 0.8531 - 518ms/epoch - 26ms/step
Epoch 569/1500
20/20 - 1s - loss: 0.3992 - categorical_accuracy: 0.8542 - val_loss: 0.4192 - val_categorical_accuracy: 0.8481 - 526ms/epoch - 26ms/step
Epoch 570/1500
20/20 - 1s - loss: 0.4141 - categorical_accuracy: 0.8496 - val_loss: 0.4093 - val_categorical_accuracy: 0.8584 - 510ms/epoch - 26ms/step
Epoch 571/1500
20/20 - 1s - loss: 0.7531 - categorical_accuracy: 0.7880 - val_loss: 0.4142 - val_categorical_accuracy: 0.8549 - 516ms/epoch - 26ms/step
Epoch 572/1500
20/20 - 1s - loss: 0.3879 - categorical_accuracy: 0.8647 - val_loss: 0.3969 - val_categorical_accuracy: 0.8621 - 502ms/epoch - 25ms/step
Epoch 573/1500
20/20 - 1s - loss: 0.3806 - categorical_accuracy: 0.8666 - val_loss: 0.3957 - val_categorical_accuracy: 0.8597 - 518ms/epoch - 26ms/step
Epoch 574/1500
20/20 - 1s - loss: 0.3769 - categorical_accuracy: 0.8673 - val_loss: 0.3880 - val_categorical_accuracy: 0.8657 - 505ms/epoch - 25ms/step
Epoch 575/1500
20/20 - 1s - loss: 0.3834 - categorical_accuracy: 0.8655 - val_loss: 0.4554 - val_categorical_accuracy: 0.8356 - 510ms/epoch - 26ms/step
Epoch 576/1500
20/20 - 0s - loss: 0.4881 - categorical_accuracy: 0.8262 - val_loss: 0.3899 - val_categorical_accuracy: 0.8637 - 496ms/epoch - 25ms/step
Epoch 577/1500
20/20 - 1s - loss: 0.3729 - categorical_accuracy: 0.8698 - val_loss: 0.3957 - val_categorical_accuracy: 0.8588 - 504ms/epoch - 25ms/step
Epoch 578/1500
20/20 - 1s - loss: 0.4066 - categorical_accuracy: 0.8492 - val_loss: 0.4330 - val_categorical_accuracy: 0.8390 - 504ms/epoch - 25ms/step
Epoch 579/1500
20/20 - 0s - loss: 0.4097 - categorical_accuracy: 0.8479 - val_loss: 0.4220 - val_categorical_accuracy: 0.8485 - 497ms/epoch - 25ms/step
Epoch 580/1500
20/20 - 1s - loss: 0.4079 - categorical_accuracy: 0.8491 - val_loss: 0.4158 - val_categorical_accuracy: 0.8484 - 503ms/epoch - 25ms/step
Epoch 581/1500
20/20 - 1s - loss: 0.3934 - categorical_accuracy: 0.8555 - val_loss: 0.4059 - val_categorical_accuracy: 0.8535 - 506ms/epoch - 25ms/step
Epoch 582/1500
20/20 - 1s - loss: 0.3942 - categorical_accuracy: 0.8565 - val_loss: 0.4490 - val_categorical_accuracy: 0.8334 - 513ms/epoch - 26ms/step
Epoch 583/1500
20/20 - 1s - loss: 0.4618 - categorical_accuracy: 0.8321 - val_loss: 0.4152 - val_categorical_accuracy: 0.8539 - 531ms/epoch - 27ms/step
Epoch 584/1500
20/20 - 1s - loss: 0.3865 - categorical_accuracy: 0.8633 - val_loss: 0.3881 - val_categorical_accuracy: 0.8630 - 517ms/epoch - 26ms/step
Epoch 585/1500
20/20 - 1s - loss: 0.3982 - categorical_accuracy: 0.8539 - val_loss: 0.4314 - val_categorical_accuracy: 0.8379 - 503ms/epoch - 25ms/step
Epoch 586/1500
20/20 - 1s - loss: 0.3967 - categorical_accuracy: 0.8532 - val_loss: 0.4090 - val_categorical_accuracy: 0.8500 - 509ms/epoch - 25ms/step
Epoch 587/1500
20/20 - 1s - loss: 0.3999 - categorical_accuracy: 0.8507 - val_loss: 0.4081 - val_categorical_accuracy: 0.8495 - 513ms/epoch - 26ms/step
Epoch 588/1500
20/20 - 1s - loss: 0.4042 - categorical_accuracy: 0.8509 - val_loss: 0.4202 - val_categorical_accuracy: 0.8437 - 503ms/epoch - 25ms/step
Epoch 589/1500
20/20 - 1s - loss: 0.3946 - categorical_accuracy: 0.8559 - val_loss: 0.4010 - val_categorical_accuracy: 0.8536 - 506ms/epoch - 25ms/step
Epoch 590/1500
20/20 - 1s - loss: 0.3965 - categorical_accuracy: 0.8561 - val_loss: 0.4536 - val_categorical_accuracy: 0.8326 - 505ms/epoch - 25ms/step
Epoch 591/1500
20/20 - 1s - loss: 0.4258 - categorical_accuracy: 0.8472 - val_loss: 0.5427 - val_categorical_accuracy: 0.8031 - 500ms/epoch - 25ms/step
Epoch 592/1500
20/20 - 0s - loss: 0.7608 - categorical_accuracy: 0.7844 - val_loss: 0.3965 - val_categorical_accuracy: 0.8609 - 498ms/epoch - 25ms/step
Epoch 593/1500
20/20 - 1s - loss: 0.3757 - categorical_accuracy: 0.8695 - val_loss: 0.3849 - val_categorical_accuracy: 0.8663 - 500ms/epoch - 25ms/step
Epoch 594/1500
20/20 - 0s - loss: 0.3701 - categorical_accuracy: 0.8711 - val_loss: 0.3893 - val_categorical_accuracy: 0.8620 - 482ms/epoch - 24ms/step
Epoch 595/1500
20/20 - 0s - loss: 0.3710 - categorical_accuracy: 0.8688 - val_loss: 0.3822 - val_categorical_accuracy: 0.8670 - 485ms/epoch - 24ms/step
Epoch 596/1500
20/20 - 0s - loss: 0.3849 - categorical_accuracy: 0.8621 - val_loss: 0.4094 - val_categorical_accuracy: 0.8524 - 481ms/epoch - 24ms/step
Epoch 597/1500
20/20 - 0s - loss: 0.3986 - categorical_accuracy: 0.8535 - val_loss: 0.4346 - val_categorical_accuracy: 0.8356 - 490ms/epoch - 25ms/step
Epoch 598/1500
20/20 - 0s - loss: 0.4069 - categorical_accuracy: 0.8477 - val_loss: 0.4251 - val_categorical_accuracy: 0.8418 - 484ms/epoch - 24ms/step
Epoch 599/1500
20/20 - 0s - loss: 0.3880 - categorical_accuracy: 0.8595 - val_loss: 0.4237 - val_categorical_accuracy: 0.8445 - 494ms/epoch - 25ms/step
Epoch 600/1500
20/20 - 0s - loss: 0.3948 - categorical_accuracy: 0.8553 - val_loss: 0.3969 - val_categorical_accuracy: 0.8548 - 489ms/epoch - 24ms/step
Epoch 601/1500
20/20 - 0s - loss: 0.3944 - categorical_accuracy: 0.8588 - val_loss: 0.4189 - val_categorical_accuracy: 0.8500 - 493ms/epoch - 25ms/step
Epoch 602/1500
20/20 - 0s - loss: 0.4336 - categorical_accuracy: 0.8453 - val_loss: 0.5043 - val_categorical_accuracy: 0.8203 - 493ms/epoch - 25ms/step
Epoch 603/1500
20/20 - 0s - loss: 0.3960 - categorical_accuracy: 0.8606 - val_loss: 0.4048 - val_categorical_accuracy: 0.8515 - 486ms/epoch - 24ms/step
Epoch 604/1500
20/20 - 0s - loss: 0.3927 - categorical_accuracy: 0.8558 - val_loss: 0.4190 - val_categorical_accuracy: 0.8452 - 487ms/epoch - 24ms/step
Epoch 605/1500
20/20 - 0s - loss: 0.3847 - categorical_accuracy: 0.8625 - val_loss: 0.3999 - val_categorical_accuracy: 0.8554 - 490ms/epoch - 25ms/step
Epoch 606/1500
20/20 - 0s - loss: 0.3843 - categorical_accuracy: 0.8617 - val_loss: 0.4090 - val_categorical_accuracy: 0.8496 - 484ms/epoch - 24ms/step
Epoch 607/1500
20/20 - 0s - loss: 0.3902 - categorical_accuracy: 0.8574 - val_loss: 0.4090 - val_categorical_accuracy: 0.8517 - 486ms/epoch - 24ms/step
Epoch 608/1500
20/20 - 0s - loss: 0.3985 - categorical_accuracy: 0.8538 - val_loss: 0.3951 - val_categorical_accuracy: 0.8607 - 472ms/epoch - 24ms/step
Epoch 609/1500
20/20 - 0s - loss: 0.3747 - categorical_accuracy: 0.8670 - val_loss: 0.3822 - val_categorical_accuracy: 0.8670 - 482ms/epoch - 24ms/step
Epoch 610/1500
20/20 - 0s - loss: 0.3872 - categorical_accuracy: 0.8590 - val_loss: 0.4447 - val_categorical_accuracy: 0.8309 - 474ms/epoch - 24ms/step
Epoch 611/1500
20/20 - 0s - loss: 0.4051 - categorical_accuracy: 0.8501 - val_loss: 0.4318 - val_categorical_accuracy: 0.8397 - 486ms/epoch - 24ms/step
Epoch 612/1500
20/20 - 0s - loss: 0.3940 - categorical_accuracy: 0.8592 - val_loss: 0.4054 - val_categorical_accuracy: 0.8548 - 480ms/epoch - 24ms/step
Epoch 613/1500
20/20 - 0s - loss: 0.3759 - categorical_accuracy: 0.8662 - val_loss: 0.3951 - val_categorical_accuracy: 0.8551 - 488ms/epoch - 24ms/step
Epoch 614/1500
20/20 - 0s - loss: 0.3878 - categorical_accuracy: 0.8571 - val_loss: 0.4118 - val_categorical_accuracy: 0.8487 - 489ms/epoch - 24ms/step
Epoch 615/1500
20/20 - 0s - loss: 0.3918 - categorical_accuracy: 0.8566 - val_loss: 0.4229 - val_categorical_accuracy: 0.8450 - 488ms/epoch - 24ms/step
Epoch 616/1500
20/20 - 0s - loss: 0.4380 - categorical_accuracy: 0.8395 - val_loss: 0.4457 - val_categorical_accuracy: 0.8390 - 487ms/epoch - 24ms/step
Epoch 617/1500
20/20 - 0s - loss: 0.3952 - categorical_accuracy: 0.8610 - val_loss: 0.4156 - val_categorical_accuracy: 0.8527 - 485ms/epoch - 24ms/step
Epoch 618/1500
20/20 - 0s - loss: 0.3775 - categorical_accuracy: 0.8678 - val_loss: 0.4104 - val_categorical_accuracy: 0.8490 - 481ms/epoch - 24ms/step
Epoch 619/1500
20/20 - 1s - loss: 0.3913 - categorical_accuracy: 0.8573 - val_loss: 0.3987 - val_categorical_accuracy: 0.8529 - 503ms/epoch - 25ms/step
Epoch 620/1500
20/20 - 0s - loss: 0.3975 - categorical_accuracy: 0.8518 - val_loss: 0.4049 - val_categorical_accuracy: 0.8538 - 473ms/epoch - 24ms/step
Epoch 621/1500
20/20 - 0s - loss: 0.3770 - categorical_accuracy: 0.8654 - val_loss: 0.3745 - val_categorical_accuracy: 0.8678 - 496ms/epoch - 25ms/step
Epoch 622/1500
20/20 - 0s - loss: 0.3603 - categorical_accuracy: 0.8720 - val_loss: 0.4346 - val_categorical_accuracy: 0.8369 - 489ms/epoch - 24ms/step
Epoch 623/1500
20/20 - 1s - loss: 0.3917 - categorical_accuracy: 0.8556 - val_loss: 0.3753 - val_categorical_accuracy: 0.8662 - 502ms/epoch - 25ms/step
Epoch 624/1500
20/20 - 0s - loss: 0.3775 - categorical_accuracy: 0.8620 - val_loss: 0.3963 - val_categorical_accuracy: 0.8560 - 486ms/epoch - 24ms/step
Epoch 625/1500
20/20 - 0s - loss: 0.4605 - categorical_accuracy: 0.8336 - val_loss: 0.5597 - val_categorical_accuracy: 0.7976 - 496ms/epoch - 25ms/step
Epoch 626/1500
20/20 - 0s - loss: 0.4081 - categorical_accuracy: 0.8529 - val_loss: 0.3794 - val_categorical_accuracy: 0.8643 - 482ms/epoch - 24ms/step
Epoch 627/1500
20/20 - 0s - loss: 0.3484 - categorical_accuracy: 0.8791 - val_loss: 0.3637 - val_categorical_accuracy: 0.8729 - 492ms/epoch - 25ms/step
Epoch 628/1500
20/20 - 0s - loss: 0.3604 - categorical_accuracy: 0.8714 - val_loss: 0.3958 - val_categorical_accuracy: 0.8545 - 494ms/epoch - 25ms/step
Epoch 629/1500
20/20 - 0s - loss: 0.3899 - categorical_accuracy: 0.8539 - val_loss: 0.4016 - val_categorical_accuracy: 0.8515 - 484ms/epoch - 24ms/step
Epoch 630/1500
20/20 - 0s - loss: 0.3740 - categorical_accuracy: 0.8628 - val_loss: 0.3862 - val_categorical_accuracy: 0.8648 - 488ms/epoch - 24ms/step
Epoch 631/1500
20/20 - 0s - loss: 0.3687 - categorical_accuracy: 0.8667 - val_loss: 0.3744 - val_categorical_accuracy: 0.8665 - 496ms/epoch - 25ms/step
Epoch 632/1500
20/20 - 0s - loss: 0.3738 - categorical_accuracy: 0.8631 - val_loss: 0.3972 - val_categorical_accuracy: 0.8575 - 494ms/epoch - 25ms/step
Epoch 633/1500
20/20 - 0s - loss: 0.3867 - categorical_accuracy: 0.8610 - val_loss: 0.3822 - val_categorical_accuracy: 0.8675 - 491ms/epoch - 25ms/step
Epoch 634/1500
20/20 - 0s - loss: 0.3879 - categorical_accuracy: 0.8577 - val_loss: 0.4569 - val_categorical_accuracy: 0.8299 - 484ms/epoch - 24ms/step
Epoch 635/1500
20/20 - 0s - loss: 0.3944 - categorical_accuracy: 0.8570 - val_loss: 0.3935 - val_categorical_accuracy: 0.8573 - 495ms/epoch - 25ms/step
Epoch 636/1500
20/20 - 1s - loss: 0.3612 - categorical_accuracy: 0.8715 - val_loss: 0.3768 - val_categorical_accuracy: 0.8665 - 504ms/epoch - 25ms/step
Epoch 637/1500
20/20 - 1s - loss: 0.3747 - categorical_accuracy: 0.8667 - val_loss: 0.4592 - val_categorical_accuracy: 0.8294 - 519ms/epoch - 26ms/step
Epoch 638/1500
20/20 - 1s - loss: 0.4870 - categorical_accuracy: 0.8242 - val_loss: 0.3815 - val_categorical_accuracy: 0.8623 - 503ms/epoch - 25ms/step
Epoch 639/1500
20/20 - 0s - loss: 0.3498 - categorical_accuracy: 0.8784 - val_loss: 0.3680 - val_categorical_accuracy: 0.8698 - 483ms/epoch - 24ms/step
Epoch 640/1500
20/20 - 0s - loss: 0.3664 - categorical_accuracy: 0.8676 - val_loss: 0.4217 - val_categorical_accuracy: 0.8410 - 482ms/epoch - 24ms/step
Epoch 641/1500
20/20 - 1s - loss: 0.3997 - categorical_accuracy: 0.8498 - val_loss: 0.3966 - val_categorical_accuracy: 0.8587 - 501ms/epoch - 25ms/step
Epoch 642/1500
20/20 - 1s - loss: 0.3589 - categorical_accuracy: 0.8735 - val_loss: 0.3770 - val_categorical_accuracy: 0.8653 - 502ms/epoch - 25ms/step
Epoch 643/1500
20/20 - 1s - loss: 0.3934 - categorical_accuracy: 0.8558 - val_loss: 0.4834 - val_categorical_accuracy: 0.8201 - 518ms/epoch - 26ms/step
Epoch 644/1500
20/20 - 1s - loss: 0.4078 - categorical_accuracy: 0.8553 - val_loss: 0.3687 - val_categorical_accuracy: 0.8687 - 526ms/epoch - 26ms/step
Epoch 645/1500
20/20 - 1s - loss: 0.3770 - categorical_accuracy: 0.8624 - val_loss: 0.4047 - val_categorical_accuracy: 0.8489 - 500ms/epoch - 25ms/step
Epoch 646/1500
20/20 - 0s - loss: 0.3741 - categorical_accuracy: 0.8632 - val_loss: 0.3851 - val_categorical_accuracy: 0.8591 - 492ms/epoch - 25ms/step
Epoch 647/1500
20/20 - 1s - loss: 0.3770 - categorical_accuracy: 0.8598 - val_loss: 0.3899 - val_categorical_accuracy: 0.8566 - 507ms/epoch - 25ms/step
Epoch 648/1500
20/20 - 0s - loss: 0.3684 - categorical_accuracy: 0.8656 - val_loss: 0.3724 - val_categorical_accuracy: 0.8682 - 486ms/epoch - 24ms/step
Epoch 649/1500
20/20 - 1s - loss: 0.3567 - categorical_accuracy: 0.8733 - val_loss: 0.3976 - val_categorical_accuracy: 0.8577 - 502ms/epoch - 25ms/step
Epoch 650/1500
20/20 - 0s - loss: 0.3743 - categorical_accuracy: 0.8649 - val_loss: 0.3746 - val_categorical_accuracy: 0.8718 - 488ms/epoch - 24ms/step
Epoch 651/1500
20/20 - 0s - loss: 0.3532 - categorical_accuracy: 0.8758 - val_loss: 0.3748 - val_categorical_accuracy: 0.8657 - 488ms/epoch - 24ms/step
Epoch 652/1500
20/20 - 0s - loss: 0.3731 - categorical_accuracy: 0.8623 - val_loss: 0.3831 - val_categorical_accuracy: 0.8602 - 489ms/epoch - 24ms/step
Epoch 653/1500
20/20 - 0s - loss: 0.3722 - categorical_accuracy: 0.8632 - val_loss: 0.4307 - val_categorical_accuracy: 0.8372 - 498ms/epoch - 25ms/step
Epoch 654/1500
20/20 - 0s - loss: 0.7147 - categorical_accuracy: 0.7879 - val_loss: 0.3759 - val_categorical_accuracy: 0.8685 - 490ms/epoch - 25ms/step
Epoch 655/1500
20/20 - 0s - loss: 0.3496 - categorical_accuracy: 0.8792 - val_loss: 0.3594 - val_categorical_accuracy: 0.8758 - 483ms/epoch - 24ms/step
Epoch 656/1500
20/20 - 0s - loss: 0.3437 - categorical_accuracy: 0.8811 - val_loss: 0.3676 - val_categorical_accuracy: 0.8699 - 496ms/epoch - 25ms/step
Epoch 657/1500
20/20 - 0s - loss: 0.3415 - categorical_accuracy: 0.8812 - val_loss: 0.3587 - val_categorical_accuracy: 0.8737 - 488ms/epoch - 24ms/step
Epoch 658/1500
20/20 - 0s - loss: 0.3534 - categorical_accuracy: 0.8740 - val_loss: 0.3672 - val_categorical_accuracy: 0.8685 - 494ms/epoch - 25ms/step
Epoch 659/1500
20/20 - 1s - loss: 0.4080 - categorical_accuracy: 0.8517 - val_loss: 0.5490 - val_categorical_accuracy: 0.8000 - 502ms/epoch - 25ms/step
Epoch 660/1500
20/20 - 0s - loss: 0.3976 - categorical_accuracy: 0.8601 - val_loss: 0.3570 - val_categorical_accuracy: 0.8740 - 490ms/epoch - 25ms/step
Epoch 661/1500
20/20 - 0s - loss: 0.3408 - categorical_accuracy: 0.8799 - val_loss: 0.3699 - val_categorical_accuracy: 0.8674 - 482ms/epoch - 24ms/step
Epoch 662/1500
20/20 - 0s - loss: 0.3661 - categorical_accuracy: 0.8655 - val_loss: 0.3788 - val_categorical_accuracy: 0.8615 - 486ms/epoch - 24ms/step
Epoch 663/1500
20/20 - 1s - loss: 0.3640 - categorical_accuracy: 0.8673 - val_loss: 0.3834 - val_categorical_accuracy: 0.8578 - 501ms/epoch - 25ms/step
Epoch 664/1500
20/20 - 0s - loss: 0.3610 - categorical_accuracy: 0.8682 - val_loss: 0.3706 - val_categorical_accuracy: 0.8658 - 488ms/epoch - 24ms/step
Epoch 665/1500
20/20 - 0s - loss: 0.3702 - categorical_accuracy: 0.8626 - val_loss: 0.3808 - val_categorical_accuracy: 0.8612 - 496ms/epoch - 25ms/step
Epoch 666/1500
20/20 - 0s - loss: 0.3710 - categorical_accuracy: 0.8627 - val_loss: 0.3912 - val_categorical_accuracy: 0.8595 - 497ms/epoch - 25ms/step
Epoch 667/1500
20/20 - 1s - loss: 0.4202 - categorical_accuracy: 0.8509 - val_loss: 0.5559 - val_categorical_accuracy: 0.8042 - 504ms/epoch - 25ms/step
Epoch 668/1500
20/20 - 1s - loss: 0.4069 - categorical_accuracy: 0.8532 - val_loss: 0.3533 - val_categorical_accuracy: 0.8770 - 509ms/epoch - 25ms/step
Epoch 669/1500
20/20 - 1s - loss: 0.3323 - categorical_accuracy: 0.8847 - val_loss: 0.3642 - val_categorical_accuracy: 0.8731 - 524ms/epoch - 26ms/step
Epoch 670/1500
20/20 - 1s - loss: 0.3685 - categorical_accuracy: 0.8657 - val_loss: 0.3891 - val_categorical_accuracy: 0.8575 - 516ms/epoch - 26ms/step
Epoch 671/1500
20/20 - 1s - loss: 0.3618 - categorical_accuracy: 0.8669 - val_loss: 0.3757 - val_categorical_accuracy: 0.8619 - 509ms/epoch - 25ms/step
Epoch 672/1500
20/20 - 1s - loss: 0.3650 - categorical_accuracy: 0.8674 - val_loss: 0.4012 - val_categorical_accuracy: 0.8533 - 528ms/epoch - 26ms/step
Epoch 673/1500
20/20 - 1s - loss: 0.3439 - categorical_accuracy: 0.8780 - val_loss: 0.3661 - val_categorical_accuracy: 0.8699 - 530ms/epoch - 27ms/step
Epoch 674/1500
20/20 - 1s - loss: 0.3593 - categorical_accuracy: 0.8692 - val_loss: 0.3936 - val_categorical_accuracy: 0.8549 - 517ms/epoch - 26ms/step
Epoch 675/1500
20/20 - 1s - loss: 0.3766 - categorical_accuracy: 0.8612 - val_loss: 0.3632 - val_categorical_accuracy: 0.8737 - 525ms/epoch - 26ms/step
Epoch 676/1500
20/20 - 0s - loss: 0.3374 - categorical_accuracy: 0.8827 - val_loss: 0.3603 - val_categorical_accuracy: 0.8729 - 494ms/epoch - 25ms/step
Epoch 677/1500
20/20 - 0s - loss: 0.3958 - categorical_accuracy: 0.8542 - val_loss: 0.4370 - val_categorical_accuracy: 0.8407 - 497ms/epoch - 25ms/step
Epoch 678/1500
20/20 - 0s - loss: 0.3597 - categorical_accuracy: 0.8701 - val_loss: 0.3597 - val_categorical_accuracy: 0.8707 - 491ms/epoch - 25ms/step
Epoch 679/1500
20/20 - 0s - loss: 0.3603 - categorical_accuracy: 0.8686 - val_loss: 0.4102 - val_categorical_accuracy: 0.8474 - 498ms/epoch - 25ms/step
Epoch 680/1500
20/20 - 0s - loss: 0.3847 - categorical_accuracy: 0.8593 - val_loss: 0.3656 - val_categorical_accuracy: 0.8686 - 483ms/epoch - 24ms/step
Epoch 681/1500
20/20 - 0s - loss: 0.3493 - categorical_accuracy: 0.8746 - val_loss: 0.3894 - val_categorical_accuracy: 0.8587 - 485ms/epoch - 24ms/step
Epoch 682/1500
20/20 - 0s - loss: 0.3921 - categorical_accuracy: 0.8558 - val_loss: 0.3847 - val_categorical_accuracy: 0.8627 - 489ms/epoch - 24ms/step
Epoch 683/1500
20/20 - 0s - loss: 0.3576 - categorical_accuracy: 0.8723 - val_loss: 0.3535 - val_categorical_accuracy: 0.8781 - 492ms/epoch - 25ms/step
Epoch 684/1500
20/20 - 0s - loss: 0.3613 - categorical_accuracy: 0.8700 - val_loss: 0.4008 - val_categorical_accuracy: 0.8520 - 492ms/epoch - 25ms/step
Epoch 685/1500
20/20 - 0s - loss: 0.3730 - categorical_accuracy: 0.8620 - val_loss: 0.3783 - val_categorical_accuracy: 0.8616 - 487ms/epoch - 24ms/step
Epoch 686/1500
20/20 - 0s - loss: 0.3464 - categorical_accuracy: 0.8747 - val_loss: 0.3549 - val_categorical_accuracy: 0.8727 - 490ms/epoch - 25ms/step
Epoch 687/1500
20/20 - 0s - loss: 0.3442 - categorical_accuracy: 0.8759 - val_loss: 0.3911 - val_categorical_accuracy: 0.8558 - 488ms/epoch - 24ms/step
Epoch 688/1500
20/20 - 0s - loss: 0.3643 - categorical_accuracy: 0.8674 - val_loss: 0.4676 - val_categorical_accuracy: 0.8257 - 488ms/epoch - 24ms/step
Epoch 689/1500
20/20 - 0s - loss: 0.4483 - categorical_accuracy: 0.8388 - val_loss: 0.4611 - val_categorical_accuracy: 0.8352 - 488ms/epoch - 24ms/step
Epoch 690/1500
20/20 - 0s - loss: 0.3443 - categorical_accuracy: 0.8807 - val_loss: 0.3390 - val_categorical_accuracy: 0.8839 - 487ms/epoch - 24ms/step
Epoch 691/1500
20/20 - 0s - loss: 0.3432 - categorical_accuracy: 0.8764 - val_loss: 0.4085 - val_categorical_accuracy: 0.8482 - 484ms/epoch - 24ms/step
Epoch 692/1500
20/20 - 0s - loss: 0.3650 - categorical_accuracy: 0.8652 - val_loss: 0.3607 - val_categorical_accuracy: 0.8719 - 483ms/epoch - 24ms/step
Epoch 693/1500
20/20 - 0s - loss: 0.3454 - categorical_accuracy: 0.8752 - val_loss: 0.3661 - val_categorical_accuracy: 0.8665 - 490ms/epoch - 24ms/step
Epoch 694/1500
20/20 - 0s - loss: 0.3680 - categorical_accuracy: 0.8647 - val_loss: 0.3997 - val_categorical_accuracy: 0.8506 - 499ms/epoch - 25ms/step
Epoch 695/1500
20/20 - 0s - loss: 0.3607 - categorical_accuracy: 0.8670 - val_loss: 0.3434 - val_categorical_accuracy: 0.8792 - 491ms/epoch - 25ms/step
Epoch 696/1500
20/20 - 0s - loss: 0.3295 - categorical_accuracy: 0.8839 - val_loss: 0.4006 - val_categorical_accuracy: 0.8533 - 488ms/epoch - 24ms/step
Epoch 697/1500
20/20 - 0s - loss: 0.4261 - categorical_accuracy: 0.8435 - val_loss: 0.4269 - val_categorical_accuracy: 0.8507 - 495ms/epoch - 25ms/step
Epoch 698/1500
20/20 - 0s - loss: 0.3573 - categorical_accuracy: 0.8759 - val_loss: 0.3420 - val_categorical_accuracy: 0.8825 - 499ms/epoch - 25ms/step
Epoch 699/1500
20/20 - 1s - loss: 0.3560 - categorical_accuracy: 0.8690 - val_loss: 0.3619 - val_categorical_accuracy: 0.8698 - 506ms/epoch - 25ms/step
Epoch 700/1500
20/20 - 0s - loss: 0.3398 - categorical_accuracy: 0.8776 - val_loss: 0.3657 - val_categorical_accuracy: 0.8661 - 486ms/epoch - 24ms/step
Epoch 701/1500
20/20 - 1s - loss: 0.3464 - categorical_accuracy: 0.8734 - val_loss: 0.3564 - val_categorical_accuracy: 0.8717 - 502ms/epoch - 25ms/step
Epoch 702/1500
20/20 - 0s - loss: 0.3397 - categorical_accuracy: 0.8780 - val_loss: 0.3942 - val_categorical_accuracy: 0.8546 - 480ms/epoch - 24ms/step
Epoch 703/1500
20/20 - 0s - loss: 0.3888 - categorical_accuracy: 0.8568 - val_loss: 0.3651 - val_categorical_accuracy: 0.8735 - 492ms/epoch - 25ms/step
Epoch 704/1500
20/20 - 0s - loss: 0.3403 - categorical_accuracy: 0.8793 - val_loss: 0.3546 - val_categorical_accuracy: 0.8736 - 481ms/epoch - 24ms/step
Epoch 705/1500
20/20 - 1s - loss: 0.3405 - categorical_accuracy: 0.8781 - val_loss: 0.3612 - val_categorical_accuracy: 0.8715 - 502ms/epoch - 25ms/step
Epoch 706/1500
20/20 - 0s - loss: 0.3562 - categorical_accuracy: 0.8736 - val_loss: 0.3812 - val_categorical_accuracy: 0.8663 - 499ms/epoch - 25ms/step
Epoch 707/1500
20/20 - 1s - loss: 0.4508 - categorical_accuracy: 0.8421 - val_loss: 0.3411 - val_categorical_accuracy: 0.8841 - 516ms/epoch - 26ms/step
Epoch 708/1500
20/20 - 0s - loss: 0.3208 - categorical_accuracy: 0.8883 - val_loss: 0.3606 - val_categorical_accuracy: 0.8714 - 489ms/epoch - 24ms/step
Epoch 709/1500
20/20 - 1s - loss: 0.3614 - categorical_accuracy: 0.8666 - val_loss: 0.3760 - val_categorical_accuracy: 0.8610 - 501ms/epoch - 25ms/step
Epoch 710/1500
20/20 - 1s - loss: 0.3551 - categorical_accuracy: 0.8700 - val_loss: 0.3648 - val_categorical_accuracy: 0.8671 - 500ms/epoch - 25ms/step
Epoch 711/1500
20/20 - 1s - loss: 0.3349 - categorical_accuracy: 0.8808 - val_loss: 0.3676 - val_categorical_accuracy: 0.8678 - 523ms/epoch - 26ms/step
Epoch 712/1500
20/20 - 1s - loss: 0.3598 - categorical_accuracy: 0.8670 - val_loss: 0.3747 - val_categorical_accuracy: 0.8620 - 504ms/epoch - 25ms/step
Epoch 713/1500
20/20 - 1s - loss: 0.3520 - categorical_accuracy: 0.8707 - val_loss: 0.3877 - val_categorical_accuracy: 0.8568 - 525ms/epoch - 26ms/step
Epoch 714/1500
20/20 - 1s - loss: 0.3465 - categorical_accuracy: 0.8760 - val_loss: 0.3584 - val_categorical_accuracy: 0.8714 - 505ms/epoch - 25ms/step
Epoch 715/1500
20/20 - 1s - loss: 0.3472 - categorical_accuracy: 0.8735 - val_loss: 0.4164 - val_categorical_accuracy: 0.8466 - 502ms/epoch - 25ms/step
Epoch 716/1500
20/20 - 1s - loss: 0.3655 - categorical_accuracy: 0.8658 - val_loss: 0.3465 - val_categorical_accuracy: 0.8775 - 504ms/epoch - 25ms/step
Epoch 717/1500
20/20 - 1s - loss: 0.3253 - categorical_accuracy: 0.8862 - val_loss: 0.3837 - val_categorical_accuracy: 0.8602 - 514ms/epoch - 26ms/step
Epoch 718/1500
20/20 - 0s - loss: 0.3406 - categorical_accuracy: 0.8783 - val_loss: 0.3807 - val_categorical_accuracy: 0.8591 - 496ms/epoch - 25ms/step
Epoch 719/1500
20/20 - 1s - loss: 0.3517 - categorical_accuracy: 0.8700 - val_loss: 0.3838 - val_categorical_accuracy: 0.8563 - 537ms/epoch - 27ms/step
Epoch 720/1500
20/20 - 1s - loss: 0.3590 - categorical_accuracy: 0.8668 - val_loss: 0.3741 - val_categorical_accuracy: 0.8659 - 539ms/epoch - 27ms/step
Epoch 721/1500
20/20 - 1s - loss: 0.3478 - categorical_accuracy: 0.8732 - val_loss: 0.3516 - val_categorical_accuracy: 0.8747 - 533ms/epoch - 27ms/step
Epoch 722/1500
20/20 - 1s - loss: 0.3282 - categorical_accuracy: 0.8829 - val_loss: 0.3466 - val_categorical_accuracy: 0.8740 - 513ms/epoch - 26ms/step
Epoch 723/1500
20/20 - 1s - loss: 0.3432 - categorical_accuracy: 0.8757 - val_loss: 0.4098 - val_categorical_accuracy: 0.8443 - 517ms/epoch - 26ms/step
Epoch 724/1500
20/20 - 1s - loss: 0.3539 - categorical_accuracy: 0.8715 - val_loss: 0.3440 - val_categorical_accuracy: 0.8777 - 505ms/epoch - 25ms/step
Epoch 725/1500
20/20 - 1s - loss: 0.3552 - categorical_accuracy: 0.8707 - val_loss: 0.3632 - val_categorical_accuracy: 0.8735 - 506ms/epoch - 25ms/step
Epoch 726/1500
20/20 - 0s - loss: 0.3832 - categorical_accuracy: 0.8648 - val_loss: 0.5546 - val_categorical_accuracy: 0.7995 - 487ms/epoch - 24ms/step
Epoch 727/1500
20/20 - 1s - loss: 0.3786 - categorical_accuracy: 0.8679 - val_loss: 0.3301 - val_categorical_accuracy: 0.8844 - 501ms/epoch - 25ms/step
Epoch 728/1500
20/20 - 1s - loss: 0.3281 - categorical_accuracy: 0.8823 - val_loss: 0.3694 - val_categorical_accuracy: 0.8640 - 501ms/epoch - 25ms/step
Epoch 729/1500
20/20 - 1s - loss: 0.3448 - categorical_accuracy: 0.8732 - val_loss: 0.3532 - val_categorical_accuracy: 0.8714 - 505ms/epoch - 25ms/step
Epoch 730/1500
20/20 - 0s - loss: 0.3291 - categorical_accuracy: 0.8819 - val_loss: 0.3739 - val_categorical_accuracy: 0.8612 - 483ms/epoch - 24ms/step
Epoch 731/1500
20/20 - 0s - loss: 0.3418 - categorical_accuracy: 0.8750 - val_loss: 0.3420 - val_categorical_accuracy: 0.8773 - 487ms/epoch - 24ms/step
Epoch 732/1500
20/20 - 0s - loss: 0.3460 - categorical_accuracy: 0.8733 - val_loss: 0.3547 - val_categorical_accuracy: 0.8710 - 498ms/epoch - 25ms/step
Epoch 733/1500
20/20 - 1s - loss: 0.3401 - categorical_accuracy: 0.8751 - val_loss: 0.3840 - val_categorical_accuracy: 0.8557 - 505ms/epoch - 25ms/step
Epoch 734/1500
20/20 - 1s - loss: 0.3371 - categorical_accuracy: 0.8780 - val_loss: 0.3442 - val_categorical_accuracy: 0.8822 - 501ms/epoch - 25ms/step
Epoch 735/1500
20/20 - 0s - loss: 0.3377 - categorical_accuracy: 0.8808 - val_loss: 0.3648 - val_categorical_accuracy: 0.8700 - 495ms/epoch - 25ms/step
Epoch 736/1500
20/20 - 0s - loss: 0.3651 - categorical_accuracy: 0.8647 - val_loss: 0.3616 - val_categorical_accuracy: 0.8678 - 499ms/epoch - 25ms/step
Epoch 737/1500
20/20 - 1s - loss: 0.3329 - categorical_accuracy: 0.8791 - val_loss: 0.3436 - val_categorical_accuracy: 0.8764 - 505ms/epoch - 25ms/step
Epoch 738/1500
20/20 - 0s - loss: 0.3301 - categorical_accuracy: 0.8803 - val_loss: 0.3674 - val_categorical_accuracy: 0.8676 - 487ms/epoch - 24ms/step
Epoch 739/1500
20/20 - 0s - loss: 0.3881 - categorical_accuracy: 0.8589 - val_loss: 0.6342 - val_categorical_accuracy: 0.7859 - 483ms/epoch - 24ms/step
Epoch 740/1500
20/20 - 0s - loss: 0.3840 - categorical_accuracy: 0.8671 - val_loss: 0.3250 - val_categorical_accuracy: 0.8895 - 485ms/epoch - 24ms/step
Epoch 741/1500
20/20 - 0s - loss: 0.3085 - categorical_accuracy: 0.8927 - val_loss: 0.3571 - val_categorical_accuracy: 0.8696 - 489ms/epoch - 24ms/step
Epoch 742/1500
20/20 - 0s - loss: 0.3456 - categorical_accuracy: 0.8722 - val_loss: 0.3594 - val_categorical_accuracy: 0.8676 - 487ms/epoch - 24ms/step
Epoch 743/1500
20/20 - 0s - loss: 0.3319 - categorical_accuracy: 0.8791 - val_loss: 0.3507 - val_categorical_accuracy: 0.8730 - 485ms/epoch - 24ms/step
Epoch 744/1500
20/20 - 0s - loss: 0.3499 - categorical_accuracy: 0.8736 - val_loss: 0.3514 - val_categorical_accuracy: 0.8783 - 484ms/epoch - 24ms/step
Epoch 745/1500
20/20 - 0s - loss: 0.3184 - categorical_accuracy: 0.8891 - val_loss: 0.3526 - val_categorical_accuracy: 0.8714 - 494ms/epoch - 25ms/step
Epoch 746/1500
20/20 - 0s - loss: 0.3544 - categorical_accuracy: 0.8702 - val_loss: 0.3593 - val_categorical_accuracy: 0.8677 - 490ms/epoch - 25ms/step
Epoch 747/1500
20/20 - 1s - loss: 0.3259 - categorical_accuracy: 0.8823 - val_loss: 0.3420 - val_categorical_accuracy: 0.8760 - 504ms/epoch - 25ms/step
Epoch 748/1500
20/20 - 0s - loss: 0.3170 - categorical_accuracy: 0.8879 - val_loss: 0.3567 - val_categorical_accuracy: 0.8681 - 488ms/epoch - 24ms/step
Epoch 749/1500
20/20 - 1s - loss: 0.4563 - categorical_accuracy: 0.8388 - val_loss: 0.3750 - val_categorical_accuracy: 0.8675 - 503ms/epoch - 25ms/step
Epoch 750/1500
20/20 - 0s - loss: 0.3057 - categorical_accuracy: 0.8952 - val_loss: 0.3227 - val_categorical_accuracy: 0.8882 - 485ms/epoch - 24ms/step
Epoch 751/1500
20/20 - 1s - loss: 0.3196 - categorical_accuracy: 0.8867 - val_loss: 0.3692 - val_categorical_accuracy: 0.8626 - 502ms/epoch - 25ms/step
Epoch 752/1500
20/20 - 0s - loss: 0.3443 - categorical_accuracy: 0.8722 - val_loss: 0.3725 - val_categorical_accuracy: 0.8623 - 485ms/epoch - 24ms/step
Epoch 753/1500
20/20 - 1s - loss: 0.3309 - categorical_accuracy: 0.8801 - val_loss: 0.3341 - val_categorical_accuracy: 0.8810 - 501ms/epoch - 25ms/step
Epoch 754/1500
20/20 - 0s - loss: 0.3395 - categorical_accuracy: 0.8753 - val_loss: 0.3611 - val_categorical_accuracy: 0.8688 - 483ms/epoch - 24ms/step
Epoch 755/1500
20/20 - 1s - loss: 0.3426 - categorical_accuracy: 0.8753 - val_loss: 0.3676 - val_categorical_accuracy: 0.8650 - 507ms/epoch - 25ms/step
Epoch 756/1500
20/20 - 0s - loss: 0.3296 - categorical_accuracy: 0.8807 - val_loss: 0.3442 - val_categorical_accuracy: 0.8739 - 490ms/epoch - 25ms/step
Epoch 757/1500
20/20 - 1s - loss: 0.3119 - categorical_accuracy: 0.8892 - val_loss: 0.3300 - val_categorical_accuracy: 0.8833 - 512ms/epoch - 26ms/step
Epoch 758/1500
20/20 - 0s - loss: 0.3250 - categorical_accuracy: 0.8824 - val_loss: 0.3424 - val_categorical_accuracy: 0.8761 - 491ms/epoch - 25ms/step
Epoch 759/1500
20/20 - 1s - loss: 0.3317 - categorical_accuracy: 0.8791 - val_loss: 0.4118 - val_categorical_accuracy: 0.8469 - 513ms/epoch - 26ms/step
Epoch 760/1500
20/20 - 0s - loss: 0.3596 - categorical_accuracy: 0.8667 - val_loss: 0.3483 - val_categorical_accuracy: 0.8746 - 477ms/epoch - 24ms/step
Epoch 761/1500
20/20 - 0s - loss: 0.3186 - categorical_accuracy: 0.8863 - val_loss: 0.3384 - val_categorical_accuracy: 0.8782 - 492ms/epoch - 25ms/step
Epoch 762/1500
20/20 - 0s - loss: 0.3291 - categorical_accuracy: 0.8800 - val_loss: 0.3557 - val_categorical_accuracy: 0.8690 - 482ms/epoch - 24ms/step
Epoch 763/1500
20/20 - 0s - loss: 0.3360 - categorical_accuracy: 0.8784 - val_loss: 0.3609 - val_categorical_accuracy: 0.8713 - 496ms/epoch - 25ms/step
Epoch 764/1500
20/20 - 0s - loss: 0.9011 - categorical_accuracy: 0.7830 - val_loss: 0.3651 - val_categorical_accuracy: 0.8742 - 488ms/epoch - 24ms/step
Epoch 765/1500
20/20 - 0s - loss: 0.3225 - categorical_accuracy: 0.8910 - val_loss: 0.3309 - val_categorical_accuracy: 0.8872 - 484ms/epoch - 24ms/step
Epoch 766/1500
20/20 - 0s - loss: 0.3064 - categorical_accuracy: 0.8962 - val_loss: 0.3212 - val_categorical_accuracy: 0.8900 - 492ms/epoch - 25ms/step
Epoch 767/1500
20/20 - 0s - loss: 0.3004 - categorical_accuracy: 0.8978 - val_loss: 0.3252 - val_categorical_accuracy: 0.8858 - 481ms/epoch - 24ms/step
Epoch 768/1500
20/20 - 0s - loss: 0.2969 - categorical_accuracy: 0.8986 - val_loss: 0.3182 - val_categorical_accuracy: 0.8907 - 490ms/epoch - 25ms/step
Epoch 769/1500
20/20 - 0s - loss: 0.3169 - categorical_accuracy: 0.8864 - val_loss: 0.3731 - val_categorical_accuracy: 0.8605 - 483ms/epoch - 24ms/step
Epoch 770/1500
20/20 - 1s - loss: 0.3367 - categorical_accuracy: 0.8762 - val_loss: 0.3448 - val_categorical_accuracy: 0.8750 - 509ms/epoch - 25ms/step
Epoch 771/1500
20/20 - 0s - loss: 0.3286 - categorical_accuracy: 0.8800 - val_loss: 0.3319 - val_categorical_accuracy: 0.8815 - 499ms/epoch - 25ms/step
Epoch 772/1500
20/20 - 0s - loss: 0.3129 - categorical_accuracy: 0.8884 - val_loss: 0.3258 - val_categorical_accuracy: 0.8850 - 497ms/epoch - 25ms/step
Epoch 773/1500
20/20 - 0s - loss: 0.3184 - categorical_accuracy: 0.8852 - val_loss: 0.3402 - val_categorical_accuracy: 0.8778 - 482ms/epoch - 24ms/step
Epoch 774/1500
20/20 - 0s - loss: 0.3246 - categorical_accuracy: 0.8834 - val_loss: 0.3304 - val_categorical_accuracy: 0.8821 - 497ms/epoch - 25ms/step
Epoch 775/1500
20/20 - 0s - loss: 0.3227 - categorical_accuracy: 0.8830 - val_loss: 0.3544 - val_categorical_accuracy: 0.8696 - 496ms/epoch - 25ms/step
Epoch 776/1500
20/20 - 0s - loss: 0.3347 - categorical_accuracy: 0.8790 - val_loss: 0.3685 - val_categorical_accuracy: 0.8684 - 499ms/epoch - 25ms/step
Epoch 777/1500
20/20 - 0s - loss: 0.3561 - categorical_accuracy: 0.8734 - val_loss: 0.3328 - val_categorical_accuracy: 0.8849 - 492ms/epoch - 25ms/step
Epoch 778/1500
20/20 - 0s - loss: 0.3320 - categorical_accuracy: 0.8801 - val_loss: 0.3572 - val_categorical_accuracy: 0.8721 - 487ms/epoch - 24ms/step
Epoch 779/1500
20/20 - 0s - loss: 0.3293 - categorical_accuracy: 0.8835 - val_loss: 0.3530 - val_categorical_accuracy: 0.8692 - 499ms/epoch - 25ms/step
Epoch 780/1500
20/20 - 0s - loss: 0.3142 - categorical_accuracy: 0.8871 - val_loss: 0.3457 - val_categorical_accuracy: 0.8736 - 480ms/epoch - 24ms/step
Epoch 781/1500
20/20 - 0s - loss: 0.3100 - categorical_accuracy: 0.8906 - val_loss: 0.3259 - val_categorical_accuracy: 0.8887 - 482ms/epoch - 24ms/step
Epoch 782/1500
20/20 - 0s - loss: 0.3231 - categorical_accuracy: 0.8845 - val_loss: 0.3811 - val_categorical_accuracy: 0.8588 - 494ms/epoch - 25ms/step
Epoch 783/1500
20/20 - 0s - loss: 0.3463 - categorical_accuracy: 0.8716 - val_loss: 0.3705 - val_categorical_accuracy: 0.8638 - 496ms/epoch - 25ms/step
Epoch 784/1500
20/20 - 0s - loss: 0.3228 - categorical_accuracy: 0.8821 - val_loss: 0.3381 - val_categorical_accuracy: 0.8779 - 495ms/epoch - 25ms/step
Epoch 785/1500
20/20 - 0s - loss: 0.3106 - categorical_accuracy: 0.8885 - val_loss: 0.3369 - val_categorical_accuracy: 0.8754 - 493ms/epoch - 25ms/step
Epoch 786/1500
20/20 - 0s - loss: 0.3633 - categorical_accuracy: 0.8668 - val_loss: 0.5482 - val_categorical_accuracy: 0.8032 - 496ms/epoch - 25ms/step
Epoch 787/1500
20/20 - 1s - loss: 0.4109 - categorical_accuracy: 0.8617 - val_loss: 0.3145 - val_categorical_accuracy: 0.8894 - 500ms/epoch - 25ms/step
Epoch 788/1500
20/20 - 0s - loss: 0.2949 - categorical_accuracy: 0.8981 - val_loss: 0.3373 - val_categorical_accuracy: 0.8786 - 499ms/epoch - 25ms/step
Epoch 789/1500
20/20 - 0s - loss: 0.3152 - categorical_accuracy: 0.8874 - val_loss: 0.3450 - val_categorical_accuracy: 0.8747 - 492ms/epoch - 25ms/step
Epoch 790/1500
20/20 - 0s - loss: 0.3244 - categorical_accuracy: 0.8816 - val_loss: 0.3582 - val_categorical_accuracy: 0.8676 - 479ms/epoch - 24ms/step
Epoch 791/1500
20/20 - 0s - loss: 0.3285 - categorical_accuracy: 0.8793 - val_loss: 0.3463 - val_categorical_accuracy: 0.8736 - 488ms/epoch - 24ms/step
Epoch 792/1500
20/20 - 0s - loss: 0.3370 - categorical_accuracy: 0.8758 - val_loss: 0.3351 - val_categorical_accuracy: 0.8798 - 485ms/epoch - 24ms/step
Epoch 793/1500
20/20 - 0s - loss: 0.3161 - categorical_accuracy: 0.8856 - val_loss: 0.3344 - val_categorical_accuracy: 0.8804 - 486ms/epoch - 24ms/step
Epoch 794/1500
20/20 - 1s - loss: 0.3134 - categorical_accuracy: 0.8871 - val_loss: 0.3483 - val_categorical_accuracy: 0.8736 - 500ms/epoch - 25ms/step
Epoch 795/1500
20/20 - 0s - loss: 0.3063 - categorical_accuracy: 0.8905 - val_loss: 0.3373 - val_categorical_accuracy: 0.8769 - 484ms/epoch - 24ms/step
Epoch 796/1500
20/20 - 0s - loss: 0.3350 - categorical_accuracy: 0.8763 - val_loss: 0.4210 - val_categorical_accuracy: 0.8431 - 490ms/epoch - 25ms/step
Epoch 797/1500
20/20 - 0s - loss: 0.3346 - categorical_accuracy: 0.8794 - val_loss: 0.3317 - val_categorical_accuracy: 0.8808 - 500ms/epoch - 25ms/step
Epoch 798/1500
20/20 - 0s - loss: 0.3104 - categorical_accuracy: 0.8882 - val_loss: 0.3429 - val_categorical_accuracy: 0.8768 - 496ms/epoch - 25ms/step
Epoch 799/1500
20/20 - 1s - loss: 0.3432 - categorical_accuracy: 0.8738 - val_loss: 0.3554 - val_categorical_accuracy: 0.8727 - 506ms/epoch - 25ms/step
Epoch 800/1500
20/20 - 1s - loss: 0.3300 - categorical_accuracy: 0.8837 - val_loss: 0.3557 - val_categorical_accuracy: 0.8726 - 502ms/epoch - 25ms/step
Epoch 801/1500
20/20 - 0s - loss: 0.3282 - categorical_accuracy: 0.8794 - val_loss: 0.3533 - val_categorical_accuracy: 0.8706 - 498ms/epoch - 25ms/step
Epoch 802/1500
20/20 - 1s - loss: 0.3150 - categorical_accuracy: 0.8851 - val_loss: 0.3299 - val_categorical_accuracy: 0.8813 - 507ms/epoch - 25ms/step
Epoch 803/1500
20/20 - 0s - loss: 0.3089 - categorical_accuracy: 0.8890 - val_loss: 0.3321 - val_categorical_accuracy: 0.8802 - 490ms/epoch - 25ms/step
Epoch 804/1500
20/20 - 0s - loss: 0.3108 - categorical_accuracy: 0.8875 - val_loss: 0.3538 - val_categorical_accuracy: 0.8699 - 484ms/epoch - 24ms/step
Epoch 805/1500
20/20 - 0s - loss: 0.3397 - categorical_accuracy: 0.8763 - val_loss: 0.3556 - val_categorical_accuracy: 0.8703 - 481ms/epoch - 24ms/step
Epoch 806/1500
20/20 - 0s - loss: 0.3169 - categorical_accuracy: 0.8857 - val_loss: 0.3272 - val_categorical_accuracy: 0.8837 - 489ms/epoch - 24ms/step
Epoch 807/1500
20/20 - 1s - loss: 0.3016 - categorical_accuracy: 0.8914 - val_loss: 0.3182 - val_categorical_accuracy: 0.8873 - 502ms/epoch - 25ms/step
Epoch 808/1500
20/20 - 1s - loss: 0.3157 - categorical_accuracy: 0.8860 - val_loss: 0.3382 - val_categorical_accuracy: 0.8785 - 510ms/epoch - 26ms/step
Epoch 809/1500
20/20 - 0s - loss: 0.3105 - categorical_accuracy: 0.8891 - val_loss: 0.3216 - val_categorical_accuracy: 0.8851 - 485ms/epoch - 24ms/step
Epoch 810/1500
20/20 - 1s - loss: 0.3054 - categorical_accuracy: 0.8905 - val_loss: 0.3245 - val_categorical_accuracy: 0.8827 - 501ms/epoch - 25ms/step
Epoch 811/1500
20/20 - 1s - loss: 0.3330 - categorical_accuracy: 0.8782 - val_loss: 0.4544 - val_categorical_accuracy: 0.8316 - 516ms/epoch - 26ms/step
Epoch 812/1500
20/20 - 1s - loss: 0.4609 - categorical_accuracy: 0.8429 - val_loss: 0.3085 - val_categorical_accuracy: 0.8924 - 501ms/epoch - 25ms/step
Epoch 813/1500
20/20 - 0s - loss: 0.2875 - categorical_accuracy: 0.9005 - val_loss: 0.3020 - val_categorical_accuracy: 0.8953 - 492ms/epoch - 25ms/step
Epoch 814/1500
20/20 - 1s - loss: 0.2965 - categorical_accuracy: 0.8959 - val_loss: 0.3298 - val_categorical_accuracy: 0.8821 - 501ms/epoch - 25ms/step
Epoch 815/1500
20/20 - 0s - loss: 0.3291 - categorical_accuracy: 0.8803 - val_loss: 0.3386 - val_categorical_accuracy: 0.8771 - 495ms/epoch - 25ms/step
Epoch 816/1500
20/20 - 0s - loss: 0.2992 - categorical_accuracy: 0.8946 - val_loss: 0.3186 - val_categorical_accuracy: 0.8881 - 486ms/epoch - 24ms/step
Epoch 817/1500
20/20 - 0s - loss: 0.3086 - categorical_accuracy: 0.8893 - val_loss: 0.3329 - val_categorical_accuracy: 0.8785 - 489ms/epoch - 24ms/step
Epoch 818/1500
20/20 - 0s - loss: 0.3214 - categorical_accuracy: 0.8826 - val_loss: 0.3519 - val_categorical_accuracy: 0.8714 - 495ms/epoch - 25ms/step
Epoch 819/1500
20/20 - 0s - loss: 0.3050 - categorical_accuracy: 0.8918 - val_loss: 0.3127 - val_categorical_accuracy: 0.8899 - 485ms/epoch - 24ms/step
Epoch 820/1500
20/20 - 0s - loss: 0.3072 - categorical_accuracy: 0.8888 - val_loss: 0.3579 - val_categorical_accuracy: 0.8711 - 494ms/epoch - 25ms/step
Epoch 821/1500
20/20 - 0s - loss: 0.3165 - categorical_accuracy: 0.8844 - val_loss: 0.3477 - val_categorical_accuracy: 0.8740 - 487ms/epoch - 24ms/step
Epoch 822/1500
20/20 - 0s - loss: 0.3071 - categorical_accuracy: 0.8894 - val_loss: 0.3373 - val_categorical_accuracy: 0.8780 - 489ms/epoch - 24ms/step
Epoch 823/1500
20/20 - 0s - loss: 0.3414 - categorical_accuracy: 0.8748 - val_loss: 0.3419 - val_categorical_accuracy: 0.8760 - 486ms/epoch - 24ms/step
Epoch 824/1500
20/20 - 0s - loss: 0.2858 - categorical_accuracy: 0.9006 - val_loss: 0.3058 - val_categorical_accuracy: 0.8922 - 486ms/epoch - 24ms/step
Epoch 825/1500
20/20 - 0s - loss: 0.3016 - categorical_accuracy: 0.8919 - val_loss: 0.3218 - val_categorical_accuracy: 0.8861 - 492ms/epoch - 25ms/step
Epoch 826/1500
20/20 - 0s - loss: 0.4053 - categorical_accuracy: 0.8624 - val_loss: 0.5630 - val_categorical_accuracy: 0.8081 - 489ms/epoch - 24ms/step
Epoch 827/1500
20/20 - 0s - loss: 0.3339 - categorical_accuracy: 0.8860 - val_loss: 0.3046 - val_categorical_accuracy: 0.8940 - 486ms/epoch - 24ms/step
Epoch 828/1500
20/20 - 0s - loss: 0.2825 - categorical_accuracy: 0.9019 - val_loss: 0.3326 - val_categorical_accuracy: 0.8794 - 486ms/epoch - 24ms/step
Epoch 829/1500
20/20 - 0s - loss: 0.3139 - categorical_accuracy: 0.8855 - val_loss: 0.3478 - val_categorical_accuracy: 0.8708 - 484ms/epoch - 24ms/step
Epoch 830/1500
20/20 - 0s - loss: 0.3239 - categorical_accuracy: 0.8798 - val_loss: 0.3238 - val_categorical_accuracy: 0.8830 - 493ms/epoch - 25ms/step
Epoch 831/1500
20/20 - 0s - loss: 0.3256 - categorical_accuracy: 0.8803 - val_loss: 0.3175 - val_categorical_accuracy: 0.8897 - 477ms/epoch - 24ms/step
Epoch 832/1500
20/20 - 0s - loss: 0.2882 - categorical_accuracy: 0.8994 - val_loss: 0.3131 - val_categorical_accuracy: 0.8885 - 495ms/epoch - 25ms/step
Epoch 833/1500
20/20 - 0s - loss: 0.3140 - categorical_accuracy: 0.8858 - val_loss: 0.3349 - val_categorical_accuracy: 0.8768 - 477ms/epoch - 24ms/step
Epoch 834/1500
20/20 - 0s - loss: 0.3149 - categorical_accuracy: 0.8851 - val_loss: 0.3597 - val_categorical_accuracy: 0.8671 - 499ms/epoch - 25ms/step
Epoch 835/1500
20/20 - 0s - loss: 0.3050 - categorical_accuracy: 0.8905 - val_loss: 0.3339 - val_categorical_accuracy: 0.8796 - 487ms/epoch - 24ms/step
Epoch 836/1500
20/20 - 1s - loss: 0.2901 - categorical_accuracy: 0.8976 - val_loss: 0.3325 - val_categorical_accuracy: 0.8805 - 502ms/epoch - 25ms/step
Epoch 837/1500
20/20 - 0s - loss: 0.3199 - categorical_accuracy: 0.8816 - val_loss: 0.3359 - val_categorical_accuracy: 0.8769 - 486ms/epoch - 24ms/step
Epoch 838/1500
20/20 - 0s - loss: 0.3115 - categorical_accuracy: 0.8861 - val_loss: 0.3160 - val_categorical_accuracy: 0.8867 - 489ms/epoch - 24ms/step
Epoch 839/1500
20/20 - 0s - loss: 0.2900 - categorical_accuracy: 0.8974 - val_loss: 0.3304 - val_categorical_accuracy: 0.8799 - 479ms/epoch - 24ms/step
Epoch 840/1500
20/20 - 1s - loss: 0.3214 - categorical_accuracy: 0.8816 - val_loss: 0.3098 - val_categorical_accuracy: 0.8922 - 514ms/epoch - 26ms/step
Epoch 841/1500
20/20 - 0s - loss: 0.2869 - categorical_accuracy: 0.9009 - val_loss: 0.3201 - val_categorical_accuracy: 0.8857 - 487ms/epoch - 24ms/step
Epoch 842/1500
20/20 - 0s - loss: 0.3154 - categorical_accuracy: 0.8837 - val_loss: 0.3203 - val_categorical_accuracy: 0.8855 - 479ms/epoch - 24ms/step
Epoch 843/1500
20/20 - 0s - loss: 0.2976 - categorical_accuracy: 0.8931 - val_loss: 0.3127 - val_categorical_accuracy: 0.8887 - 480ms/epoch - 24ms/step
Epoch 844/1500
20/20 - 0s - loss: 0.3263 - categorical_accuracy: 0.8802 - val_loss: 0.3967 - val_categorical_accuracy: 0.8532 - 486ms/epoch - 24ms/step
Epoch 845/1500
20/20 - 0s - loss: 0.3118 - categorical_accuracy: 0.8892 - val_loss: 0.3120 - val_categorical_accuracy: 0.8892 - 486ms/epoch - 24ms/step
Epoch 846/1500
20/20 - 0s - loss: 0.2782 - categorical_accuracy: 0.9048 - val_loss: 0.3172 - val_categorical_accuracy: 0.8866 - 485ms/epoch - 24ms/step
Epoch 847/1500
20/20 - 0s - loss: 0.3256 - categorical_accuracy: 0.8854 - val_loss: 0.4695 - val_categorical_accuracy: 0.8317 - 493ms/epoch - 25ms/step
Epoch 848/1500
20/20 - 0s - loss: 0.4458 - categorical_accuracy: 0.8483 - val_loss: 0.3074 - val_categorical_accuracy: 0.8910 - 492ms/epoch - 25ms/step
Epoch 849/1500
20/20 - 0s - loss: 0.2727 - categorical_accuracy: 0.9069 - val_loss: 0.2893 - val_categorical_accuracy: 0.9012 - 495ms/epoch - 25ms/step
Epoch 850/1500
20/20 - 1s - loss: 0.2719 - categorical_accuracy: 0.9065 - val_loss: 0.3320 - val_categorical_accuracy: 0.8787 - 504ms/epoch - 25ms/step
Epoch 851/1500
20/20 - 0s - loss: 0.3228 - categorical_accuracy: 0.8802 - val_loss: 0.3154 - val_categorical_accuracy: 0.8870 - 472ms/epoch - 24ms/step
Epoch 852/1500
20/20 - 0s - loss: 0.3153 - categorical_accuracy: 0.8845 - val_loss: 0.4027 - val_categorical_accuracy: 0.8469 - 478ms/epoch - 24ms/step
Epoch 853/1500
20/20 - 1s - loss: 0.3044 - categorical_accuracy: 0.8903 - val_loss: 0.2988 - val_categorical_accuracy: 0.8952 - 766ms/epoch - 38ms/step
Epoch 854/1500
20/20 - 1s - loss: 0.2843 - categorical_accuracy: 0.9001 - val_loss: 0.3083 - val_categorical_accuracy: 0.8894 - 511ms/epoch - 26ms/step
Epoch 855/1500
20/20 - 1s - loss: 0.2979 - categorical_accuracy: 0.8912 - val_loss: 0.3239 - val_categorical_accuracy: 0.8792 - 504ms/epoch - 25ms/step
Epoch 856/1500
20/20 - 0s - loss: 0.3280 - categorical_accuracy: 0.8786 - val_loss: 0.3120 - val_categorical_accuracy: 0.8886 - 484ms/epoch - 24ms/step
Epoch 857/1500
20/20 - 0s - loss: 0.2982 - categorical_accuracy: 0.8925 - val_loss: 0.3183 - val_categorical_accuracy: 0.8860 - 488ms/epoch - 24ms/step
Epoch 858/1500
20/20 - 0s - loss: 0.2907 - categorical_accuracy: 0.8964 - val_loss: 0.3321 - val_categorical_accuracy: 0.8813 - 496ms/epoch - 25ms/step
Epoch 859/1500
20/20 - 1s - loss: 0.3083 - categorical_accuracy: 0.8875 - val_loss: 0.3064 - val_categorical_accuracy: 0.8922 - 500ms/epoch - 25ms/step
Epoch 860/1500
20/20 - 0s - loss: 0.2907 - categorical_accuracy: 0.8983 - val_loss: 0.3224 - val_categorical_accuracy: 0.8859 - 484ms/epoch - 24ms/step
Epoch 861/1500
20/20 - 0s - loss: 0.3474 - categorical_accuracy: 0.8719 - val_loss: 0.3268 - val_categorical_accuracy: 0.8859 - 486ms/epoch - 24ms/step
Epoch 862/1500
20/20 - 0s - loss: 0.2796 - categorical_accuracy: 0.9034 - val_loss: 0.3012 - val_categorical_accuracy: 0.8940 - 499ms/epoch - 25ms/step
Epoch 863/1500
20/20 - 1s - loss: 0.3106 - categorical_accuracy: 0.8863 - val_loss: 0.3100 - val_categorical_accuracy: 0.8914 - 511ms/epoch - 26ms/step
Epoch 864/1500
20/20 - 0s - loss: 0.2909 - categorical_accuracy: 0.8966 - val_loss: 0.3093 - val_categorical_accuracy: 0.8900 - 493ms/epoch - 25ms/step
Epoch 865/1500
20/20 - 0s - loss: 0.3080 - categorical_accuracy: 0.8881 - val_loss: 0.3693 - val_categorical_accuracy: 0.8653 - 496ms/epoch - 25ms/step
Epoch 866/1500
20/20 - 0s - loss: 0.3004 - categorical_accuracy: 0.8921 - val_loss: 0.3375 - val_categorical_accuracy: 0.8781 - 481ms/epoch - 24ms/step
Epoch 867/1500
20/20 - 1s - loss: 0.2941 - categorical_accuracy: 0.8937 - val_loss: 0.2913 - val_categorical_accuracy: 0.8987 - 504ms/epoch - 25ms/step
Epoch 868/1500
20/20 - 0s - loss: 0.2881 - categorical_accuracy: 0.8974 - val_loss: 0.3219 - val_categorical_accuracy: 0.8843 - 484ms/epoch - 24ms/step
Epoch 869/1500
20/20 - 0s - loss: 0.3099 - categorical_accuracy: 0.8885 - val_loss: 0.3851 - val_categorical_accuracy: 0.8596 - 483ms/epoch - 24ms/step
Epoch 870/1500
20/20 - 0s - loss: 0.3049 - categorical_accuracy: 0.8936 - val_loss: 0.3131 - val_categorical_accuracy: 0.8874 - 473ms/epoch - 24ms/step
Epoch 871/1500
20/20 - 0s - loss: 0.2992 - categorical_accuracy: 0.8915 - val_loss: 0.4000 - val_categorical_accuracy: 0.8515 - 489ms/epoch - 24ms/step
Epoch 872/1500
20/20 - 0s - loss: 0.3181 - categorical_accuracy: 0.8846 - val_loss: 0.2945 - val_categorical_accuracy: 0.8960 - 491ms/epoch - 25ms/step
Epoch 873/1500
20/20 - 0s - loss: 0.2815 - categorical_accuracy: 0.9013 - val_loss: 0.3284 - val_categorical_accuracy: 0.8811 - 490ms/epoch - 25ms/step
Epoch 874/1500
20/20 - 0s - loss: 0.2999 - categorical_accuracy: 0.8921 - val_loss: 0.2988 - val_categorical_accuracy: 0.8943 - 481ms/epoch - 24ms/step
Epoch 875/1500
20/20 - 0s - loss: 0.3256 - categorical_accuracy: 0.8839 - val_loss: 0.7938 - val_categorical_accuracy: 0.7872 - 491ms/epoch - 25ms/step
Epoch 876/1500
20/20 - 1s - loss: 0.3838 - categorical_accuracy: 0.8773 - val_loss: 0.2855 - val_categorical_accuracy: 0.9023 - 501ms/epoch - 25ms/step
Epoch 877/1500
20/20 - 0s - loss: 0.2633 - categorical_accuracy: 0.9103 - val_loss: 0.2918 - val_categorical_accuracy: 0.8980 - 470ms/epoch - 24ms/step
Epoch 878/1500
20/20 - 0s - loss: 0.2927 - categorical_accuracy: 0.8952 - val_loss: 0.3329 - val_categorical_accuracy: 0.8782 - 486ms/epoch - 24ms/step
Epoch 879/1500
20/20 - 0s - loss: 0.2923 - categorical_accuracy: 0.8950 - val_loss: 0.3306 - val_categorical_accuracy: 0.8811 - 481ms/epoch - 24ms/step
Epoch 880/1500
20/20 - 0s - loss: 0.2825 - categorical_accuracy: 0.9010 - val_loss: 0.3165 - val_categorical_accuracy: 0.8859 - 482ms/epoch - 24ms/step
Epoch 881/1500
20/20 - 0s - loss: 0.3007 - categorical_accuracy: 0.8910 - val_loss: 0.3040 - val_categorical_accuracy: 0.8914 - 488ms/epoch - 24ms/step
Epoch 882/1500
20/20 - 0s - loss: 0.3052 - categorical_accuracy: 0.8898 - val_loss: 0.3419 - val_categorical_accuracy: 0.8766 - 480ms/epoch - 24ms/step
Epoch 883/1500
20/20 - 0s - loss: 0.2860 - categorical_accuracy: 0.9000 - val_loss: 0.2979 - val_categorical_accuracy: 0.8949 - 479ms/epoch - 24ms/step
Epoch 884/1500
20/20 - 0s - loss: 0.2753 - categorical_accuracy: 0.9032 - val_loss: 0.3025 - val_categorical_accuracy: 0.8926 - 491ms/epoch - 25ms/step
Epoch 885/1500
20/20 - 0s - loss: 0.3128 - categorical_accuracy: 0.8854 - val_loss: 0.4015 - val_categorical_accuracy: 0.8510 - 492ms/epoch - 25ms/step
Epoch 886/1500
20/20 - 0s - loss: 0.2959 - categorical_accuracy: 0.8958 - val_loss: 0.2840 - val_categorical_accuracy: 0.9012 - 487ms/epoch - 24ms/step
Epoch 887/1500
20/20 - 0s - loss: 0.3010 - categorical_accuracy: 0.8911 - val_loss: 0.3704 - val_categorical_accuracy: 0.8625 - 474ms/epoch - 24ms/step
Epoch 888/1500
20/20 - 0s - loss: 0.3042 - categorical_accuracy: 0.8905 - val_loss: 0.2952 - val_categorical_accuracy: 0.9008 - 486ms/epoch - 24ms/step
Epoch 889/1500
20/20 - 1s - loss: 0.2806 - categorical_accuracy: 0.9031 - val_loss: 0.2936 - val_categorical_accuracy: 0.8995 - 507ms/epoch - 25ms/step
Epoch 890/1500
20/20 - 1s - loss: 0.2981 - categorical_accuracy: 0.8941 - val_loss: 0.3205 - val_categorical_accuracy: 0.8850 - 500ms/epoch - 25ms/step
Epoch 891/1500
20/20 - 0s - loss: 0.3073 - categorical_accuracy: 0.8881 - val_loss: 0.3179 - val_categorical_accuracy: 0.8845 - 491ms/epoch - 25ms/step
Epoch 892/1500
20/20 - 0s - loss: 0.3054 - categorical_accuracy: 0.8877 - val_loss: 0.3422 - val_categorical_accuracy: 0.8735 - 483ms/epoch - 24ms/step
Epoch 893/1500
20/20 - 0s - loss: 0.2722 - categorical_accuracy: 0.9047 - val_loss: 0.2889 - val_categorical_accuracy: 0.8987 - 473ms/epoch - 24ms/step
Epoch 894/1500
20/20 - 1s - loss: 0.2905 - categorical_accuracy: 0.8954 - val_loss: 0.3114 - val_categorical_accuracy: 0.8879 - 501ms/epoch - 25ms/step
Epoch 895/1500
20/20 - 0s - loss: 0.2852 - categorical_accuracy: 0.8980 - val_loss: 0.3617 - val_categorical_accuracy: 0.8678 - 492ms/epoch - 25ms/step
Epoch 896/1500
20/20 - 0s - loss: 0.4166 - categorical_accuracy: 0.8599 - val_loss: 0.2858 - val_categorical_accuracy: 0.9019 - 487ms/epoch - 24ms/step
Epoch 897/1500
20/20 - 0s - loss: 0.2713 - categorical_accuracy: 0.9056 - val_loss: 0.3078 - val_categorical_accuracy: 0.8895 - 478ms/epoch - 24ms/step
Epoch 898/1500
20/20 - 0s - loss: 0.2735 - categorical_accuracy: 0.9042 - val_loss: 0.3315 - val_categorical_accuracy: 0.8768 - 495ms/epoch - 25ms/step
Epoch 899/1500
20/20 - 0s - loss: 0.3160 - categorical_accuracy: 0.8840 - val_loss: 0.3011 - val_categorical_accuracy: 0.8947 - 496ms/epoch - 25ms/step
Epoch 900/1500
20/20 - 0s - loss: 0.2720 - categorical_accuracy: 0.9051 - val_loss: 0.2975 - val_categorical_accuracy: 0.8939 - 476ms/epoch - 24ms/step
Epoch 901/1500
20/20 - 0s - loss: 0.2669 - categorical_accuracy: 0.9072 - val_loss: 0.3063 - val_categorical_accuracy: 0.8903 - 488ms/epoch - 24ms/step
Epoch 902/1500
20/20 - 1s - loss: 0.3215 - categorical_accuracy: 0.8815 - val_loss: 0.3218 - val_categorical_accuracy: 0.8829 - 501ms/epoch - 25ms/step
Epoch 903/1500
20/20 - 0s - loss: 0.2748 - categorical_accuracy: 0.9025 - val_loss: 0.2970 - val_categorical_accuracy: 0.8948 - 496ms/epoch - 25ms/step
Epoch 904/1500
20/20 - 0s - loss: 0.2744 - categorical_accuracy: 0.9025 - val_loss: 0.3558 - val_categorical_accuracy: 0.8685 - 488ms/epoch - 24ms/step
Epoch 905/1500
20/20 - 0s - loss: 0.3157 - categorical_accuracy: 0.8842 - val_loss: 0.3052 - val_categorical_accuracy: 0.8919 - 484ms/epoch - 24ms/step
Epoch 906/1500
20/20 - 0s - loss: 0.2689 - categorical_accuracy: 0.9065 - val_loss: 0.3237 - val_categorical_accuracy: 0.8835 - 470ms/epoch - 24ms/step
Epoch 907/1500
20/20 - 0s - loss: 0.3194 - categorical_accuracy: 0.8823 - val_loss: 0.3079 - val_categorical_accuracy: 0.8899 - 496ms/epoch - 25ms/step
Epoch 908/1500
20/20 - 0s - loss: 0.2964 - categorical_accuracy: 0.8916 - val_loss: 0.3226 - val_categorical_accuracy: 0.8800 - 489ms/epoch - 24ms/step
Epoch 909/1500
20/20 - 0s - loss: 0.2798 - categorical_accuracy: 0.9001 - val_loss: 0.2863 - val_categorical_accuracy: 0.9010 - 488ms/epoch - 24ms/step
Epoch 910/1500
20/20 - 1s - loss: 0.2821 - categorical_accuracy: 0.8995 - val_loss: 0.2976 - val_categorical_accuracy: 0.8932 - 500ms/epoch - 25ms/step
Epoch 911/1500
20/20 - 0s - loss: 0.2736 - categorical_accuracy: 0.9027 - val_loss: 0.3113 - val_categorical_accuracy: 0.8857 - 497ms/epoch - 25ms/step
Epoch 912/1500
20/20 - 0s - loss: 0.3015 - categorical_accuracy: 0.8914 - val_loss: 0.3007 - val_categorical_accuracy: 0.8961 - 495ms/epoch - 25ms/step
Epoch 913/1500
20/20 - 0s - loss: 0.2708 - categorical_accuracy: 0.9075 - val_loss: 0.3502 - val_categorical_accuracy: 0.8712 - 481ms/epoch - 24ms/step
Epoch 914/1500
20/20 - 0s - loss: 0.2997 - categorical_accuracy: 0.8905 - val_loss: 0.3297 - val_categorical_accuracy: 0.8798 - 479ms/epoch - 24ms/step
Epoch 915/1500
20/20 - 1s - loss: 0.3195 - categorical_accuracy: 0.8838 - val_loss: 0.2869 - val_categorical_accuracy: 0.9022 - 518ms/epoch - 26ms/step
Epoch 916/1500
20/20 - 1s - loss: 0.2737 - categorical_accuracy: 0.9052 - val_loss: 0.3104 - val_categorical_accuracy: 0.8865 - 515ms/epoch - 26ms/step
Epoch 917/1500
20/20 - 0s - loss: 0.2736 - categorical_accuracy: 0.9028 - val_loss: 0.2759 - val_categorical_accuracy: 0.9048 - 490ms/epoch - 25ms/step
Epoch 918/1500
20/20 - 0s - loss: 0.2745 - categorical_accuracy: 0.9024 - val_loss: 0.3577 - val_categorical_accuracy: 0.8668 - 497ms/epoch - 25ms/step
Epoch 919/1500
20/20 - 0s - loss: 0.2900 - categorical_accuracy: 0.8945 - val_loss: 0.3063 - val_categorical_accuracy: 0.8897 - 493ms/epoch - 25ms/step
Epoch 920/1500
20/20 - 1s - loss: 0.2689 - categorical_accuracy: 0.9059 - val_loss: 0.3018 - val_categorical_accuracy: 0.8929 - 504ms/epoch - 25ms/step
Epoch 921/1500
20/20 - 0s - loss: 0.2903 - categorical_accuracy: 0.8951 - val_loss: 0.3145 - val_categorical_accuracy: 0.8853 - 479ms/epoch - 24ms/step
Epoch 922/1500
20/20 - 0s - loss: 0.4449 - categorical_accuracy: 0.8477 - val_loss: 0.4517 - val_categorical_accuracy: 0.8484 - 497ms/epoch - 25ms/step
Epoch 923/1500
20/20 - 0s - loss: 0.2700 - categorical_accuracy: 0.9088 - val_loss: 0.2765 - val_categorical_accuracy: 0.9054 - 482ms/epoch - 24ms/step
Epoch 924/1500
20/20 - 0s - loss: 0.2517 - categorical_accuracy: 0.9147 - val_loss: 0.2847 - val_categorical_accuracy: 0.9013 - 491ms/epoch - 25ms/step
Epoch 925/1500
20/20 - 0s - loss: 0.2790 - categorical_accuracy: 0.9000 - val_loss: 0.3038 - val_categorical_accuracy: 0.8915 - 487ms/epoch - 24ms/step
Epoch 926/1500
20/20 - 0s - loss: 0.2894 - categorical_accuracy: 0.8947 - val_loss: 0.3007 - val_categorical_accuracy: 0.8935 - 490ms/epoch - 25ms/step
Epoch 927/1500
20/20 - 0s - loss: 0.2714 - categorical_accuracy: 0.9040 - val_loss: 0.2933 - val_categorical_accuracy: 0.8955 - 492ms/epoch - 25ms/step
Epoch 928/1500
20/20 - 0s - loss: 0.2667 - categorical_accuracy: 0.9062 - val_loss: 0.3063 - val_categorical_accuracy: 0.8934 - 497ms/epoch - 25ms/step
Epoch 929/1500
20/20 - 0s - loss: 0.2861 - categorical_accuracy: 0.8973 - val_loss: 0.2861 - val_categorical_accuracy: 0.8995 - 487ms/epoch - 24ms/step
Epoch 930/1500
20/20 - 0s - loss: 0.2929 - categorical_accuracy: 0.8934 - val_loss: 0.3568 - val_categorical_accuracy: 0.8679 - 488ms/epoch - 24ms/step
Epoch 931/1500
20/20 - 0s - loss: 0.3063 - categorical_accuracy: 0.8880 - val_loss: 0.3227 - val_categorical_accuracy: 0.8819 - 479ms/epoch - 24ms/step
Epoch 932/1500
20/20 - 0s - loss: 0.2747 - categorical_accuracy: 0.9023 - val_loss: 0.2866 - val_categorical_accuracy: 0.8984 - 484ms/epoch - 24ms/step
Epoch 933/1500
20/20 - 0s - loss: 0.2602 - categorical_accuracy: 0.9103 - val_loss: 0.3014 - val_categorical_accuracy: 0.8924 - 486ms/epoch - 24ms/step
Epoch 934/1500
20/20 - 0s - loss: 0.2827 - categorical_accuracy: 0.8982 - val_loss: 0.2962 - val_categorical_accuracy: 0.8973 - 474ms/epoch - 24ms/step
Epoch 935/1500
20/20 - 0s - loss: 0.3975 - categorical_accuracy: 0.8706 - val_loss: 0.2974 - val_categorical_accuracy: 0.8991 - 477ms/epoch - 24ms/step
Epoch 936/1500
20/20 - 0s - loss: 0.2514 - categorical_accuracy: 0.9151 - val_loss: 0.2715 - val_categorical_accuracy: 0.9073 - 486ms/epoch - 24ms/step
Epoch 937/1500
20/20 - 0s - loss: 0.2790 - categorical_accuracy: 0.9002 - val_loss: 0.3232 - val_categorical_accuracy: 0.8830 - 487ms/epoch - 24ms/step
Epoch 938/1500
20/20 - 1s - loss: 0.2741 - categorical_accuracy: 0.9045 - val_loss: 0.2727 - val_categorical_accuracy: 0.9062 - 509ms/epoch - 25ms/step
Epoch 939/1500
20/20 - 0s - loss: 0.2668 - categorical_accuracy: 0.9057 - val_loss: 0.2733 - val_categorical_accuracy: 0.9052 - 475ms/epoch - 24ms/step
Epoch 940/1500
20/20 - 0s - loss: 0.2632 - categorical_accuracy: 0.9075 - val_loss: 0.3199 - val_categorical_accuracy: 0.8812 - 479ms/epoch - 24ms/step
Epoch 941/1500
20/20 - 0s - loss: 0.2970 - categorical_accuracy: 0.8903 - val_loss: 0.3310 - val_categorical_accuracy: 0.8784 - 489ms/epoch - 24ms/step
Epoch 942/1500
20/20 - 1s - loss: 0.2724 - categorical_accuracy: 0.9024 - val_loss: 0.2815 - val_categorical_accuracy: 0.9015 - 508ms/epoch - 25ms/step
Epoch 943/1500
20/20 - 0s - loss: 0.2900 - categorical_accuracy: 0.8941 - val_loss: 0.3408 - val_categorical_accuracy: 0.8742 - 493ms/epoch - 25ms/step
Epoch 944/1500
20/20 - 0s - loss: 0.2818 - categorical_accuracy: 0.8981 - val_loss: 0.2943 - val_categorical_accuracy: 0.8948 - 487ms/epoch - 24ms/step
Epoch 945/1500
20/20 - 0s - loss: 0.2567 - categorical_accuracy: 0.9107 - val_loss: 0.2813 - val_categorical_accuracy: 0.9015 - 479ms/epoch - 24ms/step
Epoch 946/1500
20/20 - 1s - loss: 0.2742 - categorical_accuracy: 0.9019 - val_loss: 0.3236 - val_categorical_accuracy: 0.8822 - 509ms/epoch - 25ms/step
Epoch 947/1500
20/20 - 0s - loss: 0.3000 - categorical_accuracy: 0.8894 - val_loss: 0.2772 - val_categorical_accuracy: 0.9023 - 477ms/epoch - 24ms/step
Epoch 948/1500
20/20 - 0s - loss: 0.2433 - categorical_accuracy: 0.9183 - val_loss: 0.2740 - val_categorical_accuracy: 0.9042 - 487ms/epoch - 24ms/step
Epoch 949/1500
20/20 - 0s - loss: 0.2769 - categorical_accuracy: 0.9013 - val_loss: 0.3220 - val_categorical_accuracy: 0.8838 - 485ms/epoch - 24ms/step
Epoch 950/1500
20/20 - 0s - loss: 0.2862 - categorical_accuracy: 0.8958 - val_loss: 0.2924 - val_categorical_accuracy: 0.8957 - 483ms/epoch - 24ms/step
Epoch 951/1500
20/20 - 1s - loss: 0.2664 - categorical_accuracy: 0.9055 - val_loss: 0.3104 - val_categorical_accuracy: 0.8858 - 504ms/epoch - 25ms/step
Epoch 952/1500
20/20 - 0s - loss: 0.2804 - categorical_accuracy: 0.8989 - val_loss: 0.2774 - val_categorical_accuracy: 0.9033 - 487ms/epoch - 24ms/step
Epoch 953/1500
20/20 - 0s - loss: 0.2517 - categorical_accuracy: 0.9138 - val_loss: 0.2912 - val_categorical_accuracy: 0.9008 - 483ms/epoch - 24ms/step
Epoch 954/1500
20/20 - 0s - loss: 0.4406 - categorical_accuracy: 0.8604 - val_loss: 0.4968 - val_categorical_accuracy: 0.8280 - 487ms/epoch - 24ms/step
Epoch 955/1500
20/20 - 1s - loss: 0.9610 - categorical_accuracy: 0.8029 - val_loss: 0.3028 - val_categorical_accuracy: 0.8982 - 505ms/epoch - 25ms/step
Epoch 956/1500
20/20 - 0s - loss: 0.2700 - categorical_accuracy: 0.9105 - val_loss: 0.2857 - val_categorical_accuracy: 0.9023 - 480ms/epoch - 24ms/step
Epoch 957/1500
20/20 - 0s - loss: 0.2563 - categorical_accuracy: 0.9153 - val_loss: 0.2757 - val_categorical_accuracy: 0.9058 - 474ms/epoch - 24ms/step
Epoch 958/1500
20/20 - 0s - loss: 0.2488 - categorical_accuracy: 0.9175 - val_loss: 0.2688 - val_categorical_accuracy: 0.9093 - 482ms/epoch - 24ms/step
Epoch 959/1500
20/20 - 0s - loss: 0.2441 - categorical_accuracy: 0.9186 - val_loss: 0.2672 - val_categorical_accuracy: 0.9093 - 482ms/epoch - 24ms/step
Epoch 960/1500
20/20 - 0s - loss: 0.2428 - categorical_accuracy: 0.9188 - val_loss: 0.2752 - val_categorical_accuracy: 0.9050 - 490ms/epoch - 25ms/step
Epoch 961/1500
20/20 - 0s - loss: 0.2689 - categorical_accuracy: 0.9048 - val_loss: 0.3062 - val_categorical_accuracy: 0.8840 - 482ms/epoch - 24ms/step
Epoch 962/1500
20/20 - 0s - loss: 0.2563 - categorical_accuracy: 0.9108 - val_loss: 0.2842 - val_categorical_accuracy: 0.8988 - 495ms/epoch - 25ms/step
Epoch 963/1500
20/20 - 0s - loss: 0.2809 - categorical_accuracy: 0.8980 - val_loss: 0.3337 - val_categorical_accuracy: 0.8760 - 489ms/epoch - 24ms/step
Epoch 964/1500
20/20 - 1s - loss: 0.2772 - categorical_accuracy: 0.8999 - val_loss: 0.2960 - val_categorical_accuracy: 0.8945 - 510ms/epoch - 26ms/step
Epoch 965/1500
20/20 - 0s - loss: 0.2722 - categorical_accuracy: 0.9026 - val_loss: 0.3271 - val_categorical_accuracy: 0.8806 - 487ms/epoch - 24ms/step
Epoch 966/1500
20/20 - 0s - loss: 0.2814 - categorical_accuracy: 0.8989 - val_loss: 0.2839 - val_categorical_accuracy: 0.8996 - 487ms/epoch - 24ms/step
Epoch 967/1500
20/20 - 0s - loss: 0.2602 - categorical_accuracy: 0.9086 - val_loss: 0.3479 - val_categorical_accuracy: 0.8759 - 488ms/epoch - 24ms/step
Epoch 968/1500
20/20 - 0s - loss: 0.2685 - categorical_accuracy: 0.9051 - val_loss: 0.3121 - val_categorical_accuracy: 0.8886 - 499ms/epoch - 25ms/step
Epoch 969/1500
20/20 - 0s - loss: 0.2730 - categorical_accuracy: 0.9012 - val_loss: 0.3070 - val_categorical_accuracy: 0.8893 - 489ms/epoch - 24ms/step
Epoch 970/1500
20/20 - 0s - loss: 0.2793 - categorical_accuracy: 0.8977 - val_loss: 0.3361 - val_categorical_accuracy: 0.8755 - 490ms/epoch - 25ms/step
Epoch 971/1500
20/20 - 0s - loss: 0.2848 - categorical_accuracy: 0.8976 - val_loss: 0.2711 - val_categorical_accuracy: 0.9058 - 486ms/epoch - 24ms/step
Epoch 972/1500
20/20 - 0s - loss: 0.2652 - categorical_accuracy: 0.9064 - val_loss: 0.2880 - val_categorical_accuracy: 0.8951 - 488ms/epoch - 24ms/step
Epoch 973/1500
20/20 - 1s - loss: 0.2572 - categorical_accuracy: 0.9091 - val_loss: 0.2838 - val_categorical_accuracy: 0.8978 - 504ms/epoch - 25ms/step
Epoch 974/1500
20/20 - 1s - loss: 0.2586 - categorical_accuracy: 0.9087 - val_loss: 0.2915 - val_categorical_accuracy: 0.8954 - 504ms/epoch - 25ms/step
Epoch 975/1500
20/20 - 0s - loss: 0.2605 - categorical_accuracy: 0.9084 - val_loss: 0.3135 - val_categorical_accuracy: 0.8843 - 490ms/epoch - 25ms/step
Epoch 976/1500
20/20 - 0s - loss: 0.2957 - categorical_accuracy: 0.8908 - val_loss: 0.3029 - val_categorical_accuracy: 0.8898 - 471ms/epoch - 24ms/step
Epoch 977/1500
20/20 - 1s - loss: 0.2894 - categorical_accuracy: 0.8947 - val_loss: 0.2949 - val_categorical_accuracy: 0.8953 - 504ms/epoch - 25ms/step
Epoch 978/1500
20/20 - 0s - loss: 0.2602 - categorical_accuracy: 0.9084 - val_loss: 0.2928 - val_categorical_accuracy: 0.8957 - 488ms/epoch - 24ms/step
Epoch 979/1500
20/20 - 0s - loss: 0.2678 - categorical_accuracy: 0.9065 - val_loss: 0.2904 - val_categorical_accuracy: 0.8960 - 493ms/epoch - 25ms/step
Epoch 980/1500
20/20 - 1s - loss: 0.2587 - categorical_accuracy: 0.9094 - val_loss: 0.3020 - val_categorical_accuracy: 0.8913 - 500ms/epoch - 25ms/step
Epoch 981/1500
20/20 - 1s - loss: 0.2837 - categorical_accuracy: 0.8964 - val_loss: 0.3201 - val_categorical_accuracy: 0.8816 - 516ms/epoch - 26ms/step
Epoch 982/1500
20/20 - 1s - loss: 0.2737 - categorical_accuracy: 0.9024 - val_loss: 0.2915 - val_categorical_accuracy: 0.8976 - 508ms/epoch - 25ms/step
Epoch 983/1500
20/20 - 0s - loss: 0.2746 - categorical_accuracy: 0.9016 - val_loss: 0.3147 - val_categorical_accuracy: 0.8826 - 492ms/epoch - 25ms/step
Epoch 984/1500
20/20 - 0s - loss: 0.2697 - categorical_accuracy: 0.9023 - val_loss: 0.2820 - val_categorical_accuracy: 0.8989 - 488ms/epoch - 24ms/step
Epoch 985/1500
20/20 - 0s - loss: 0.2543 - categorical_accuracy: 0.9111 - val_loss: 0.2903 - val_categorical_accuracy: 0.8962 - 488ms/epoch - 24ms/step
Epoch 986/1500
20/20 - 0s - loss: 0.2794 - categorical_accuracy: 0.8990 - val_loss: 0.2909 - val_categorical_accuracy: 0.8957 - 494ms/epoch - 25ms/step
Epoch 987/1500
20/20 - 1s - loss: 0.2712 - categorical_accuracy: 0.9031 - val_loss: 0.2646 - val_categorical_accuracy: 0.9085 - 503ms/epoch - 25ms/step
Epoch 988/1500
20/20 - 0s - loss: 0.2670 - categorical_accuracy: 0.9071 - val_loss: 0.3040 - val_categorical_accuracy: 0.8960 - 497ms/epoch - 25ms/step
Epoch 989/1500
20/20 - 1s - loss: 0.3574 - categorical_accuracy: 0.8806 - val_loss: 0.6854 - val_categorical_accuracy: 0.7964 - 512ms/epoch - 26ms/step
Epoch 990/1500
20/20 - 1s - loss: 0.3343 - categorical_accuracy: 0.8940 - val_loss: 0.2591 - val_categorical_accuracy: 0.9119 - 511ms/epoch - 26ms/step
Epoch 991/1500
20/20 - 0s - loss: 0.2298 - categorical_accuracy: 0.9237 - val_loss: 0.2584 - val_categorical_accuracy: 0.9119 - 480ms/epoch - 24ms/step
Epoch 992/1500
20/20 - 0s - loss: 0.2418 - categorical_accuracy: 0.9169 - val_loss: 0.2885 - val_categorical_accuracy: 0.8960 - 496ms/epoch - 25ms/step
Epoch 993/1500
20/20 - 0s - loss: 0.2674 - categorical_accuracy: 0.9039 - val_loss: 0.3336 - val_categorical_accuracy: 0.8754 - 488ms/epoch - 24ms/step
Epoch 994/1500
20/20 - 1s - loss: 0.3016 - categorical_accuracy: 0.8875 - val_loss: 0.2878 - val_categorical_accuracy: 0.8976 - 509ms/epoch - 25ms/step
Epoch 995/1500
20/20 - 1s - loss: 0.2507 - categorical_accuracy: 0.9125 - val_loss: 0.3174 - val_categorical_accuracy: 0.8849 - 514ms/epoch - 26ms/step
Epoch 996/1500
20/20 - 1s - loss: 0.2686 - categorical_accuracy: 0.9042 - val_loss: 0.2832 - val_categorical_accuracy: 0.8994 - 516ms/epoch - 26ms/step
Epoch 997/1500
20/20 - 1s - loss: 0.2637 - categorical_accuracy: 0.9063 - val_loss: 0.2937 - val_categorical_accuracy: 0.8960 - 502ms/epoch - 25ms/step
Epoch 998/1500
20/20 - 1s - loss: 0.2609 - categorical_accuracy: 0.9070 - val_loss: 0.2854 - val_categorical_accuracy: 0.8985 - 523ms/epoch - 26ms/step
Epoch 999/1500
20/20 - 1s - loss: 0.2857 - categorical_accuracy: 0.8946 - val_loss: 0.3077 - val_categorical_accuracy: 0.8901 - 519ms/epoch - 26ms/step
Epoch 1000/1500
20/20 - 1s - loss: 0.2644 - categorical_accuracy: 0.9065 - val_loss: 0.2756 - val_categorical_accuracy: 0.9023 - 510ms/epoch - 26ms/step
Epoch 1001/1500
20/20 - 0s - loss: 0.2578 - categorical_accuracy: 0.9081 - val_loss: 0.2907 - val_categorical_accuracy: 0.8956 - 497ms/epoch - 25ms/step
Epoch 1002/1500
20/20 - 1s - loss: 0.2860 - categorical_accuracy: 0.8952 - val_loss: 0.2947 - val_categorical_accuracy: 0.8962 - 505ms/epoch - 25ms/step
Epoch 1003/1500
20/20 - 1s - loss: 0.2464 - categorical_accuracy: 0.9156 - val_loss: 0.2775 - val_categorical_accuracy: 0.9013 - 516ms/epoch - 26ms/step
Epoch 1004/1500
20/20 - 1s - loss: 0.2589 - categorical_accuracy: 0.9082 - val_loss: 0.2958 - val_categorical_accuracy: 0.8886 - 502ms/epoch - 25ms/step
Epoch 1005/1500
20/20 - 0s - loss: 0.2485 - categorical_accuracy: 0.9133 - val_loss: 0.2744 - val_categorical_accuracy: 0.9046 - 490ms/epoch - 25ms/step
Epoch 1006/1500
20/20 - 1s - loss: 0.2630 - categorical_accuracy: 0.9064 - val_loss: 0.3515 - val_categorical_accuracy: 0.8698 - 509ms/epoch - 25ms/step
Epoch 1007/1500
20/20 - 1s - loss: 0.2991 - categorical_accuracy: 0.8889 - val_loss: 0.2922 - val_categorical_accuracy: 0.8953 - 516ms/epoch - 26ms/step
Epoch 1008/1500
20/20 - 1s - loss: 0.2366 - categorical_accuracy: 0.9194 - val_loss: 0.2566 - val_categorical_accuracy: 0.9114 - 520ms/epoch - 26ms/step
Epoch 1009/1500
20/20 - 1s - loss: 0.2457 - categorical_accuracy: 0.9156 - val_loss: 0.3547 - val_categorical_accuracy: 0.8723 - 505ms/epoch - 25ms/step
Epoch 1010/1500
20/20 - 0s - loss: 0.3029 - categorical_accuracy: 0.8893 - val_loss: 0.2811 - val_categorical_accuracy: 0.8996 - 493ms/epoch - 25ms/step
Epoch 1011/1500
20/20 - 1s - loss: 0.2689 - categorical_accuracy: 0.9060 - val_loss: 0.5078 - val_categorical_accuracy: 0.8225 - 502ms/epoch - 25ms/step
Epoch 1012/1500
20/20 - 1s - loss: 0.4229 - categorical_accuracy: 0.8702 - val_loss: 0.2560 - val_categorical_accuracy: 0.9126 - 502ms/epoch - 25ms/step
Epoch 1013/1500
20/20 - 0s - loss: 0.2266 - categorical_accuracy: 0.9247 - val_loss: 0.2575 - val_categorical_accuracy: 0.9117 - 476ms/epoch - 24ms/step
Epoch 1014/1500
20/20 - 0s - loss: 0.2602 - categorical_accuracy: 0.9079 - val_loss: 0.3252 - val_categorical_accuracy: 0.8829 - 484ms/epoch - 24ms/step
Epoch 1015/1500
20/20 - 0s - loss: 0.2594 - categorical_accuracy: 0.9078 - val_loss: 0.2731 - val_categorical_accuracy: 0.9038 - 486ms/epoch - 24ms/step
Epoch 1016/1500
20/20 - 0s - loss: 0.2481 - categorical_accuracy: 0.9130 - val_loss: 0.2757 - val_categorical_accuracy: 0.9023 - 499ms/epoch - 25ms/step
Epoch 1017/1500
20/20 - 0s - loss: 0.2787 - categorical_accuracy: 0.8973 - val_loss: 0.2915 - val_categorical_accuracy: 0.8953 - 483ms/epoch - 24ms/step
Epoch 1018/1500
20/20 - 0s - loss: 0.2515 - categorical_accuracy: 0.9109 - val_loss: 0.2795 - val_categorical_accuracy: 0.9019 - 492ms/epoch - 25ms/step
Epoch 1019/1500
20/20 - 0s - loss: 0.2601 - categorical_accuracy: 0.9076 - val_loss: 0.2866 - val_categorical_accuracy: 0.8973 - 495ms/epoch - 25ms/step
Epoch 1020/1500
20/20 - 0s - loss: 0.2434 - categorical_accuracy: 0.9150 - val_loss: 0.2695 - val_categorical_accuracy: 0.9044 - 489ms/epoch - 24ms/step
Epoch 1021/1500
20/20 - 1s - loss: 0.2620 - categorical_accuracy: 0.9067 - val_loss: 0.2748 - val_categorical_accuracy: 0.9013 - 504ms/epoch - 25ms/step
Epoch 1022/1500
20/20 - 0s - loss: 0.2506 - categorical_accuracy: 0.9114 - val_loss: 0.3059 - val_categorical_accuracy: 0.8866 - 484ms/epoch - 24ms/step
Epoch 1023/1500
20/20 - 0s - loss: 0.2922 - categorical_accuracy: 0.8909 - val_loss: 0.2980 - val_categorical_accuracy: 0.8915 - 480ms/epoch - 24ms/step
Epoch 1024/1500
20/20 - 0s - loss: 0.2360 - categorical_accuracy: 0.9190 - val_loss: 0.2523 - val_categorical_accuracy: 0.9142 - 484ms/epoch - 24ms/step
Epoch 1025/1500
20/20 - 0s - loss: 0.2494 - categorical_accuracy: 0.9118 - val_loss: 0.3069 - val_categorical_accuracy: 0.8894 - 493ms/epoch - 25ms/step
Epoch 1026/1500
20/20 - 1s - loss: 0.2612 - categorical_accuracy: 0.9069 - val_loss: 0.2723 - val_categorical_accuracy: 0.9047 - 500ms/epoch - 25ms/step
Epoch 1027/1500
20/20 - 0s - loss: 0.2591 - categorical_accuracy: 0.9103 - val_loss: 0.3033 - val_categorical_accuracy: 0.8923 - 484ms/epoch - 24ms/step
Epoch 1028/1500
20/20 - 0s - loss: 0.2688 - categorical_accuracy: 0.9045 - val_loss: 0.2882 - val_categorical_accuracy: 0.8959 - 490ms/epoch - 25ms/step
Epoch 1029/1500
20/20 - 0s - loss: 0.2703 - categorical_accuracy: 0.9016 - val_loss: 0.2692 - val_categorical_accuracy: 0.9063 - 492ms/epoch - 25ms/step
Epoch 1030/1500
20/20 - 1s - loss: 0.2470 - categorical_accuracy: 0.9138 - val_loss: 0.2709 - val_categorical_accuracy: 0.9048 - 501ms/epoch - 25ms/step
Epoch 1031/1500
20/20 - 0s - loss: 0.2593 - categorical_accuracy: 0.9075 - val_loss: 0.2708 - val_categorical_accuracy: 0.9042 - 479ms/epoch - 24ms/step
Epoch 1032/1500
20/20 - 0s - loss: 0.2525 - categorical_accuracy: 0.9107 - val_loss: 0.3057 - val_categorical_accuracy: 0.8904 - 466ms/epoch - 23ms/step
Epoch 1033/1500
20/20 - 0s - loss: 0.2674 - categorical_accuracy: 0.9034 - val_loss: 0.2640 - val_categorical_accuracy: 0.9075 - 471ms/epoch - 24ms/step
Epoch 1034/1500
20/20 - 0s - loss: 0.2551 - categorical_accuracy: 0.9098 - val_loss: 0.3001 - val_categorical_accuracy: 0.8901 - 474ms/epoch - 24ms/step
Epoch 1035/1500
20/20 - 0s - loss: 0.2838 - categorical_accuracy: 0.8947 - val_loss: 0.2849 - val_categorical_accuracy: 0.8968 - 488ms/epoch - 24ms/step
Epoch 1036/1500
20/20 - 0s - loss: 0.2474 - categorical_accuracy: 0.9129 - val_loss: 0.2663 - val_categorical_accuracy: 0.9070 - 469ms/epoch - 23ms/step
Epoch 1037/1500
20/20 - 0s - loss: 0.2454 - categorical_accuracy: 0.9159 - val_loss: 0.3025 - val_categorical_accuracy: 0.8911 - 455ms/epoch - 23ms/step
Epoch 1038/1500
20/20 - 0s - loss: 0.2433 - categorical_accuracy: 0.9162 - val_loss: 0.2968 - val_categorical_accuracy: 0.8944 - 464ms/epoch - 23ms/step
Epoch 1039/1500
20/20 - 0s - loss: 0.2827 - categorical_accuracy: 0.8966 - val_loss: 0.2811 - val_categorical_accuracy: 0.9000 - 465ms/epoch - 23ms/step
Epoch 1040/1500
20/20 - 0s - loss: 0.2313 - categorical_accuracy: 0.9212 - val_loss: 0.2484 - val_categorical_accuracy: 0.9158 - 463ms/epoch - 23ms/step
Epoch 1041/1500
20/20 - 0s - loss: 0.2537 - categorical_accuracy: 0.9094 - val_loss: 0.3405 - val_categorical_accuracy: 0.8757 - 462ms/epoch - 23ms/step
Epoch 1042/1500
20/20 - 0s - loss: 0.2785 - categorical_accuracy: 0.8977 - val_loss: 0.2520 - val_categorical_accuracy: 0.9132 - 470ms/epoch - 24ms/step
Epoch 1043/1500
20/20 - 0s - loss: 0.2399 - categorical_accuracy: 0.9168 - val_loss: 0.2817 - val_categorical_accuracy: 0.8996 - 460ms/epoch - 23ms/step
Epoch 1044/1500
20/20 - 0s - loss: 0.2615 - categorical_accuracy: 0.9076 - val_loss: 0.2522 - val_categorical_accuracy: 0.9133 - 474ms/epoch - 24ms/step
Epoch 1045/1500
20/20 - 0s - loss: 0.2363 - categorical_accuracy: 0.9193 - val_loss: 0.2942 - val_categorical_accuracy: 0.8941 - 466ms/epoch - 23ms/step
Epoch 1046/1500
20/20 - 0s - loss: 0.2780 - categorical_accuracy: 0.8971 - val_loss: 0.2719 - val_categorical_accuracy: 0.9038 - 470ms/epoch - 24ms/step
Epoch 1047/1500
20/20 - 0s - loss: 0.2332 - categorical_accuracy: 0.9200 - val_loss: 0.2783 - val_categorical_accuracy: 0.9004 - 474ms/epoch - 24ms/step
Epoch 1048/1500
20/20 - 0s - loss: 0.3325 - categorical_accuracy: 0.8806 - val_loss: 0.7690 - val_categorical_accuracy: 0.7722 - 460ms/epoch - 23ms/step
Epoch 1049/1500
20/20 - 0s - loss: 0.3496 - categorical_accuracy: 0.8952 - val_loss: 0.2545 - val_categorical_accuracy: 0.9123 - 468ms/epoch - 23ms/step
Epoch 1050/1500
20/20 - 0s - loss: 0.2211 - categorical_accuracy: 0.9261 - val_loss: 0.2454 - val_categorical_accuracy: 0.9161 - 466ms/epoch - 23ms/step
Epoch 1051/1500
20/20 - 0s - loss: 0.2216 - categorical_accuracy: 0.9259 - val_loss: 0.2642 - val_categorical_accuracy: 0.9070 - 476ms/epoch - 24ms/step
Epoch 1052/1500
20/20 - 0s - loss: 0.2629 - categorical_accuracy: 0.9056 - val_loss: 0.2784 - val_categorical_accuracy: 0.9022 - 459ms/epoch - 23ms/step
Epoch 1053/1500
20/20 - 0s - loss: 0.2312 - categorical_accuracy: 0.9215 - val_loss: 0.2461 - val_categorical_accuracy: 0.9155 - 460ms/epoch - 23ms/step
Epoch 1054/1500
20/20 - 0s - loss: 0.2288 - categorical_accuracy: 0.9218 - val_loss: 0.3270 - val_categorical_accuracy: 0.8796 - 488ms/epoch - 24ms/step
Epoch 1055/1500
20/20 - 0s - loss: 0.3204 - categorical_accuracy: 0.8799 - val_loss: 0.2962 - val_categorical_accuracy: 0.8945 - 463ms/epoch - 23ms/step
Epoch 1056/1500
20/20 - 0s - loss: 0.2411 - categorical_accuracy: 0.9156 - val_loss: 0.2559 - val_categorical_accuracy: 0.9110 - 474ms/epoch - 24ms/step
Epoch 1057/1500
20/20 - 0s - loss: 0.2401 - categorical_accuracy: 0.9161 - val_loss: 0.2983 - val_categorical_accuracy: 0.8942 - 472ms/epoch - 24ms/step
Epoch 1058/1500
20/20 - 0s - loss: 0.2562 - categorical_accuracy: 0.9081 - val_loss: 0.2817 - val_categorical_accuracy: 0.9001 - 486ms/epoch - 24ms/step
Epoch 1059/1500
20/20 - 0s - loss: 0.2359 - categorical_accuracy: 0.9186 - val_loss: 0.2535 - val_categorical_accuracy: 0.9122 - 486ms/epoch - 24ms/step
Epoch 1060/1500
20/20 - 0s - loss: 0.2535 - categorical_accuracy: 0.9101 - val_loss: 0.3069 - val_categorical_accuracy: 0.8889 - 477ms/epoch - 24ms/step
Epoch 1061/1500
20/20 - 0s - loss: 0.2611 - categorical_accuracy: 0.9064 - val_loss: 0.2574 - val_categorical_accuracy: 0.9108 - 470ms/epoch - 24ms/step
Epoch 1062/1500
20/20 - 0s - loss: 0.2202 - categorical_accuracy: 0.9263 - val_loss: 0.2835 - val_categorical_accuracy: 0.8982 - 475ms/epoch - 24ms/step
Epoch 1063/1500
20/20 - 1s - loss: 0.2527 - categorical_accuracy: 0.9100 - val_loss: 0.2870 - val_categorical_accuracy: 0.8985 - 500ms/epoch - 25ms/step
Epoch 1064/1500
20/20 - 0s - loss: 0.2549 - categorical_accuracy: 0.9073 - val_loss: 0.3096 - val_categorical_accuracy: 0.8884 - 494ms/epoch - 25ms/step
Epoch 1065/1500
20/20 - 0s - loss: 0.2782 - categorical_accuracy: 0.8979 - val_loss: 0.2840 - val_categorical_accuracy: 0.8991 - 490ms/epoch - 25ms/step
Epoch 1066/1500
20/20 - 0s - loss: 0.2215 - categorical_accuracy: 0.9249 - val_loss: 0.2616 - val_categorical_accuracy: 0.9080 - 480ms/epoch - 24ms/step
Epoch 1067/1500
20/20 - 1s - loss: 0.2705 - categorical_accuracy: 0.9011 - val_loss: 0.3453 - val_categorical_accuracy: 0.8730 - 508ms/epoch - 25ms/step
Epoch 1068/1500
20/20 - 0s - loss: 0.2631 - categorical_accuracy: 0.9069 - val_loss: 0.2538 - val_categorical_accuracy: 0.9126 - 485ms/epoch - 24ms/step
Epoch 1069/1500
20/20 - 0s - loss: 0.2191 - categorical_accuracy: 0.9261 - val_loss: 0.2570 - val_categorical_accuracy: 0.9091 - 478ms/epoch - 24ms/step
Epoch 1070/1500
20/20 - 0s - loss: 0.2533 - categorical_accuracy: 0.9093 - val_loss: 0.3473 - val_categorical_accuracy: 0.8724 - 483ms/epoch - 24ms/step
Epoch 1071/1500
20/20 - 0s - loss: 0.4770 - categorical_accuracy: 0.8521 - val_loss: 0.2596 - val_categorical_accuracy: 0.9096 - 488ms/epoch - 24ms/step
Epoch 1072/1500
20/20 - 0s - loss: 0.2179 - categorical_accuracy: 0.9274 - val_loss: 0.2435 - val_categorical_accuracy: 0.9173 - 497ms/epoch - 25ms/step
Epoch 1073/1500
20/20 - 0s - loss: 0.2179 - categorical_accuracy: 0.9270 - val_loss: 0.2596 - val_categorical_accuracy: 0.9093 - 487ms/epoch - 24ms/step
Epoch 1074/1500
20/20 - 0s - loss: 0.2270 - categorical_accuracy: 0.9223 - val_loss: 0.2723 - val_categorical_accuracy: 0.9038 - 488ms/epoch - 24ms/step
Epoch 1075/1500
20/20 - 0s - loss: 0.2419 - categorical_accuracy: 0.9152 - val_loss: 0.3003 - val_categorical_accuracy: 0.8933 - 486ms/epoch - 24ms/step
Epoch 1076/1500
20/20 - 1s - loss: 0.3004 - categorical_accuracy: 0.8876 - val_loss: 0.3046 - val_categorical_accuracy: 0.8895 - 502ms/epoch - 25ms/step
Epoch 1077/1500
20/20 - 1s - loss: 0.2345 - categorical_accuracy: 0.9185 - val_loss: 0.2446 - val_categorical_accuracy: 0.9155 - 504ms/epoch - 25ms/step
Epoch 1078/1500
20/20 - 0s - loss: 0.2167 - categorical_accuracy: 0.9268 - val_loss: 0.2528 - val_categorical_accuracy: 0.9121 - 489ms/epoch - 24ms/step
Epoch 1079/1500
20/20 - 0s - loss: 0.2667 - categorical_accuracy: 0.9028 - val_loss: 0.3342 - val_categorical_accuracy: 0.8780 - 493ms/epoch - 25ms/step
Epoch 1080/1500
20/20 - 0s - loss: 0.2480 - categorical_accuracy: 0.9120 - val_loss: 0.2624 - val_categorical_accuracy: 0.9069 - 493ms/epoch - 25ms/step
Epoch 1081/1500
20/20 - 1s - loss: 0.2278 - categorical_accuracy: 0.9218 - val_loss: 0.2486 - val_categorical_accuracy: 0.9152 - 508ms/epoch - 25ms/step
Epoch 1082/1500
20/20 - 0s - loss: 0.2449 - categorical_accuracy: 0.9127 - val_loss: 0.2950 - val_categorical_accuracy: 0.8896 - 488ms/epoch - 24ms/step
Epoch 1083/1500
20/20 - 0s - loss: 0.2574 - categorical_accuracy: 0.9062 - val_loss: 0.2534 - val_categorical_accuracy: 0.9119 - 489ms/epoch - 24ms/step
Epoch 1084/1500
20/20 - 0s - loss: 0.2302 - categorical_accuracy: 0.9200 - val_loss: 0.2629 - val_categorical_accuracy: 0.9082 - 491ms/epoch - 25ms/step
Epoch 1085/1500
20/20 - 1s - loss: 0.2431 - categorical_accuracy: 0.9150 - val_loss: 0.2646 - val_categorical_accuracy: 0.9104 - 550ms/epoch - 27ms/step
Epoch 1086/1500
20/20 - 0s - loss: 0.2447 - categorical_accuracy: 0.9140 - val_loss: 0.3516 - val_categorical_accuracy: 0.8711 - 485ms/epoch - 24ms/step
Epoch 1087/1500
20/20 - 0s - loss: 0.2714 - categorical_accuracy: 0.9019 - val_loss: 0.2616 - val_categorical_accuracy: 0.9083 - 480ms/epoch - 24ms/step
Epoch 1088/1500
20/20 - 1s - loss: 0.2413 - categorical_accuracy: 0.9149 - val_loss: 0.2704 - val_categorical_accuracy: 0.9016 - 502ms/epoch - 25ms/step
Epoch 1089/1500
20/20 - 1s - loss: 0.2589 - categorical_accuracy: 0.9048 - val_loss: 0.2878 - val_categorical_accuracy: 0.8940 - 507ms/epoch - 25ms/step
Epoch 1090/1500
20/20 - 1s - loss: 0.2549 - categorical_accuracy: 0.9082 - val_loss: 0.2452 - val_categorical_accuracy: 0.9171 - 514ms/epoch - 26ms/step
Epoch 1091/1500
20/20 - 0s - loss: 0.2198 - categorical_accuracy: 0.9251 - val_loss: 0.2561 - val_categorical_accuracy: 0.9096 - 481ms/epoch - 24ms/step
Epoch 1092/1500
20/20 - 0s - loss: 0.2259 - categorical_accuracy: 0.9225 - val_loss: 0.2664 - val_categorical_accuracy: 0.9046 - 499ms/epoch - 25ms/step
Epoch 1093/1500
20/20 - 0s - loss: 0.2430 - categorical_accuracy: 0.9128 - val_loss: 0.2527 - val_categorical_accuracy: 0.9116 - 484ms/epoch - 24ms/step
Epoch 1094/1500
20/20 - 1s - loss: 0.2921 - categorical_accuracy: 0.8932 - val_loss: 0.3008 - val_categorical_accuracy: 0.8899 - 505ms/epoch - 25ms/step
Epoch 1095/1500
20/20 - 0s - loss: 0.2353 - categorical_accuracy: 0.9180 - val_loss: 0.2525 - val_categorical_accuracy: 0.9145 - 488ms/epoch - 24ms/step
Epoch 1096/1500
20/20 - 0s - loss: 0.2453 - categorical_accuracy: 0.9163 - val_loss: 0.2664 - val_categorical_accuracy: 0.9094 - 489ms/epoch - 24ms/step
Epoch 1097/1500
20/20 - 0s - loss: 0.2261 - categorical_accuracy: 0.9231 - val_loss: 0.2772 - val_categorical_accuracy: 0.9008 - 478ms/epoch - 24ms/step
Epoch 1098/1500
20/20 - 0s - loss: 0.2575 - categorical_accuracy: 0.9074 - val_loss: 0.2500 - val_categorical_accuracy: 0.9129 - 489ms/epoch - 24ms/step
Epoch 1099/1500
20/20 - 0s - loss: 0.2384 - categorical_accuracy: 0.9155 - val_loss: 0.2893 - val_categorical_accuracy: 0.8929 - 486ms/epoch - 24ms/step
Epoch 1100/1500
20/20 - 0s - loss: 0.2585 - categorical_accuracy: 0.9057 - val_loss: 0.3943 - val_categorical_accuracy: 0.8517 - 473ms/epoch - 24ms/step
Epoch 1101/1500
20/20 - 0s - loss: 0.3706 - categorical_accuracy: 0.8853 - val_loss: 0.2367 - val_categorical_accuracy: 0.9194 - 491ms/epoch - 25ms/step
Epoch 1102/1500
20/20 - 0s - loss: 0.2075 - categorical_accuracy: 0.9315 - val_loss: 0.2362 - val_categorical_accuracy: 0.9199 - 498ms/epoch - 25ms/step
Epoch 1103/1500
20/20 - 1s - loss: 0.2131 - categorical_accuracy: 0.9286 - val_loss: 0.3076 - val_categorical_accuracy: 0.8890 - 509ms/epoch - 25ms/step
Epoch 1104/1500
20/20 - 0s - loss: 0.2638 - categorical_accuracy: 0.9050 - val_loss: 0.2724 - val_categorical_accuracy: 0.9024 - 489ms/epoch - 24ms/step
Epoch 1105/1500
20/20 - 0s - loss: 0.2274 - categorical_accuracy: 0.9206 - val_loss: 0.2475 - val_categorical_accuracy: 0.9147 - 483ms/epoch - 24ms/step
Epoch 1106/1500
20/20 - 1s - loss: 0.2418 - categorical_accuracy: 0.9141 - val_loss: 0.2974 - val_categorical_accuracy: 0.8925 - 518ms/epoch - 26ms/step
Epoch 1107/1500
20/20 - 1s - loss: 0.2428 - categorical_accuracy: 0.9138 - val_loss: 0.2570 - val_categorical_accuracy: 0.9097 - 503ms/epoch - 25ms/step
Epoch 1108/1500
20/20 - 0s - loss: 0.2219 - categorical_accuracy: 0.9235 - val_loss: 0.2739 - val_categorical_accuracy: 0.9028 - 492ms/epoch - 25ms/step
Epoch 1109/1500
20/20 - 1s - loss: 0.2611 - categorical_accuracy: 0.9045 - val_loss: 0.3493 - val_categorical_accuracy: 0.8731 - 507ms/epoch - 25ms/step
Epoch 1110/1500
20/20 - 0s - loss: 0.2827 - categorical_accuracy: 0.8970 - val_loss: 0.2735 - val_categorical_accuracy: 0.9033 - 494ms/epoch - 25ms/step
Epoch 1111/1500
20/20 - 1s - loss: 0.2207 - categorical_accuracy: 0.9253 - val_loss: 0.2437 - val_categorical_accuracy: 0.9154 - 501ms/epoch - 25ms/step
Epoch 1112/1500
20/20 - 1s - loss: 0.2344 - categorical_accuracy: 0.9170 - val_loss: 0.2945 - val_categorical_accuracy: 0.8930 - 500ms/epoch - 25ms/step
Epoch 1113/1500
20/20 - 0s - loss: 0.2605 - categorical_accuracy: 0.9078 - val_loss: 0.2510 - val_categorical_accuracy: 0.9130 - 488ms/epoch - 24ms/step
Epoch 1114/1500
20/20 - 0s - loss: 0.2202 - categorical_accuracy: 0.9245 - val_loss: 0.3199 - val_categorical_accuracy: 0.8841 - 494ms/epoch - 25ms/step
Epoch 1115/1500
20/20 - 0s - loss: 0.2705 - categorical_accuracy: 0.9010 - val_loss: 0.2795 - val_categorical_accuracy: 0.9006 - 481ms/epoch - 24ms/step
Epoch 1116/1500
20/20 - 1s - loss: 0.2324 - categorical_accuracy: 0.9204 - val_loss: 0.2702 - val_categorical_accuracy: 0.9037 - 500ms/epoch - 25ms/step
Epoch 1117/1500
20/20 - 0s - loss: 0.2263 - categorical_accuracy: 0.9210 - val_loss: 0.2598 - val_categorical_accuracy: 0.9083 - 496ms/epoch - 25ms/step
Epoch 1118/1500
20/20 - 0s - loss: 0.2463 - categorical_accuracy: 0.9104 - val_loss: 0.2848 - val_categorical_accuracy: 0.8989 - 486ms/epoch - 24ms/step
Epoch 1119/1500
20/20 - 0s - loss: 0.2348 - categorical_accuracy: 0.9163 - val_loss: 0.2318 - val_categorical_accuracy: 0.9216 - 476ms/epoch - 24ms/step
Epoch 1120/1500
20/20 - 0s - loss: 0.2034 - categorical_accuracy: 0.9322 - val_loss: 0.2530 - val_categorical_accuracy: 0.9107 - 485ms/epoch - 24ms/step
Epoch 1121/1500
20/20 - 0s - loss: 0.2740 - categorical_accuracy: 0.8997 - val_loss: 0.2782 - val_categorical_accuracy: 0.8996 - 481ms/epoch - 24ms/step
Epoch 1122/1500
20/20 - 0s - loss: 0.2421 - categorical_accuracy: 0.9142 - val_loss: 0.2707 - val_categorical_accuracy: 0.9040 - 478ms/epoch - 24ms/step
Epoch 1123/1500
20/20 - 0s - loss: 0.2292 - categorical_accuracy: 0.9200 - val_loss: 0.2633 - val_categorical_accuracy: 0.9086 - 469ms/epoch - 23ms/step
Epoch 1124/1500
20/20 - 0s - loss: 0.2291 - categorical_accuracy: 0.9207 - val_loss: 0.2448 - val_categorical_accuracy: 0.9149 - 472ms/epoch - 24ms/step
Epoch 1125/1500
20/20 - 0s - loss: 0.2202 - categorical_accuracy: 0.9239 - val_loss: 0.2560 - val_categorical_accuracy: 0.9087 - 488ms/epoch - 24ms/step
Epoch 1126/1500
20/20 - 0s - loss: 0.2728 - categorical_accuracy: 0.8998 - val_loss: 0.3808 - val_categorical_accuracy: 0.8613 - 474ms/epoch - 24ms/step
Epoch 1127/1500
20/20 - 0s - loss: 0.9879 - categorical_accuracy: 0.7792 - val_loss: 0.2993 - val_categorical_accuracy: 0.8983 - 473ms/epoch - 24ms/step
Epoch 1128/1500
20/20 - 0s - loss: 0.2391 - categorical_accuracy: 0.9211 - val_loss: 0.2526 - val_categorical_accuracy: 0.9153 - 473ms/epoch - 24ms/step
Epoch 1129/1500
20/20 - 0s - loss: 0.2209 - categorical_accuracy: 0.9277 - val_loss: 0.2452 - val_categorical_accuracy: 0.9170 - 491ms/epoch - 25ms/step
Epoch 1130/1500
20/20 - 0s - loss: 0.2130 - categorical_accuracy: 0.9299 - val_loss: 0.2430 - val_categorical_accuracy: 0.9178 - 489ms/epoch - 24ms/step
Epoch 1131/1500
20/20 - 0s - loss: 0.2076 - categorical_accuracy: 0.9323 - val_loss: 0.2363 - val_categorical_accuracy: 0.9201 - 473ms/epoch - 24ms/step
Epoch 1132/1500
20/20 - 0s - loss: 0.2061 - categorical_accuracy: 0.9323 - val_loss: 0.2363 - val_categorical_accuracy: 0.9199 - 478ms/epoch - 24ms/step
Epoch 1133/1500
20/20 - 0s - loss: 0.2140 - categorical_accuracy: 0.9279 - val_loss: 0.2497 - val_categorical_accuracy: 0.9135 - 490ms/epoch - 24ms/step
Epoch 1134/1500
20/20 - 0s - loss: 0.2219 - categorical_accuracy: 0.9233 - val_loss: 0.2733 - val_categorical_accuracy: 0.9020 - 483ms/epoch - 24ms/step
Epoch 1135/1500
20/20 - 0s - loss: 0.2219 - categorical_accuracy: 0.9241 - val_loss: 0.2455 - val_categorical_accuracy: 0.9146 - 481ms/epoch - 24ms/step
Epoch 1136/1500
20/20 - 0s - loss: 0.2321 - categorical_accuracy: 0.9180 - val_loss: 0.2908 - val_categorical_accuracy: 0.8966 - 468ms/epoch - 23ms/step
Epoch 1137/1500
20/20 - 0s - loss: 0.2390 - categorical_accuracy: 0.9144 - val_loss: 0.2669 - val_categorical_accuracy: 0.9052 - 466ms/epoch - 23ms/step
Epoch 1138/1500
20/20 - 0s - loss: 0.2204 - categorical_accuracy: 0.9240 - val_loss: 0.2787 - val_categorical_accuracy: 0.8998 - 481ms/epoch - 24ms/step
Epoch 1139/1500
20/20 - 0s - loss: 0.2771 - categorical_accuracy: 0.8980 - val_loss: 0.2939 - val_categorical_accuracy: 0.8934 - 479ms/epoch - 24ms/step
Epoch 1140/1500
20/20 - 0s - loss: 0.2205 - categorical_accuracy: 0.9240 - val_loss: 0.2340 - val_categorical_accuracy: 0.9203 - 479ms/epoch - 24ms/step
Epoch 1141/1500
20/20 - 0s - loss: 0.2250 - categorical_accuracy: 0.9224 - val_loss: 0.2807 - val_categorical_accuracy: 0.8993 - 464ms/epoch - 23ms/step
Epoch 1142/1500
20/20 - 0s - loss: 0.2488 - categorical_accuracy: 0.9113 - val_loss: 0.2449 - val_categorical_accuracy: 0.9150 - 467ms/epoch - 23ms/step
Epoch 1143/1500
20/20 - 0s - loss: 0.2077 - categorical_accuracy: 0.9299 - val_loss: 0.2633 - val_categorical_accuracy: 0.9072 - 496ms/epoch - 25ms/step
Epoch 1144/1500
20/20 - 0s - loss: 0.2712 - categorical_accuracy: 0.9005 - val_loss: 0.2751 - val_categorical_accuracy: 0.9017 - 475ms/epoch - 24ms/step
Epoch 1145/1500
20/20 - 0s - loss: 0.2338 - categorical_accuracy: 0.9167 - val_loss: 0.2608 - val_categorical_accuracy: 0.9084 - 474ms/epoch - 24ms/step
Epoch 1146/1500
20/20 - 0s - loss: 0.2374 - categorical_accuracy: 0.9158 - val_loss: 0.2514 - val_categorical_accuracy: 0.9120 - 474ms/epoch - 24ms/step
Epoch 1147/1500
20/20 - 0s - loss: 0.2321 - categorical_accuracy: 0.9179 - val_loss: 0.2670 - val_categorical_accuracy: 0.9050 - 473ms/epoch - 24ms/step
Epoch 1148/1500
20/20 - 1s - loss: 0.2454 - categorical_accuracy: 0.9125 - val_loss: 0.2550 - val_categorical_accuracy: 0.9093 - 504ms/epoch - 25ms/step
Epoch 1149/1500
20/20 - 0s - loss: 0.2226 - categorical_accuracy: 0.9224 - val_loss: 0.2408 - val_categorical_accuracy: 0.9168 - 470ms/epoch - 24ms/step
Epoch 1150/1500
20/20 - 0s - loss: 0.2076 - categorical_accuracy: 0.9297 - val_loss: 0.2638 - val_categorical_accuracy: 0.9074 - 470ms/epoch - 24ms/step
Epoch 1151/1500
20/20 - 0s - loss: 0.2560 - categorical_accuracy: 0.9056 - val_loss: 0.3196 - val_categorical_accuracy: 0.8842 - 468ms/epoch - 23ms/step
Epoch 1152/1500
20/20 - 0s - loss: 0.2560 - categorical_accuracy: 0.9069 - val_loss: 0.2640 - val_categorical_accuracy: 0.9062 - 472ms/epoch - 24ms/step
Epoch 1153/1500
20/20 - 0s - loss: 0.2084 - categorical_accuracy: 0.9295 - val_loss: 0.2477 - val_categorical_accuracy: 0.9132 - 464ms/epoch - 23ms/step
Epoch 1154/1500
20/20 - 0s - loss: 0.2737 - categorical_accuracy: 0.9020 - val_loss: 0.4671 - val_categorical_accuracy: 0.8385 - 469ms/epoch - 23ms/step
Epoch 1155/1500
20/20 - 0s - loss: 0.3365 - categorical_accuracy: 0.9007 - val_loss: 0.2332 - val_categorical_accuracy: 0.9198 - 464ms/epoch - 23ms/step
Epoch 1156/1500
20/20 - 0s - loss: 0.1995 - categorical_accuracy: 0.9336 - val_loss: 0.2328 - val_categorical_accuracy: 0.9197 - 470ms/epoch - 24ms/step
Epoch 1157/1500
20/20 - 0s - loss: 0.2021 - categorical_accuracy: 0.9331 - val_loss: 0.2481 - val_categorical_accuracy: 0.9129 - 476ms/epoch - 24ms/step
Epoch 1158/1500
20/20 - 0s - loss: 0.2594 - categorical_accuracy: 0.9064 - val_loss: 0.2784 - val_categorical_accuracy: 0.9005 - 469ms/epoch - 23ms/step
Epoch 1159/1500
20/20 - 0s - loss: 0.2227 - categorical_accuracy: 0.9225 - val_loss: 0.2641 - val_categorical_accuracy: 0.9055 - 472ms/epoch - 24ms/step
Epoch 1160/1500
20/20 - 0s - loss: 0.2479 - categorical_accuracy: 0.9090 - val_loss: 0.3190 - val_categorical_accuracy: 0.8855 - 461ms/epoch - 23ms/step
Epoch 1161/1500
20/20 - 0s - loss: 0.2304 - categorical_accuracy: 0.9189 - val_loss: 0.2431 - val_categorical_accuracy: 0.9154 - 479ms/epoch - 24ms/step
Epoch 1162/1500
20/20 - 0s - loss: 0.2108 - categorical_accuracy: 0.9284 - val_loss: 0.2717 - val_categorical_accuracy: 0.9027 - 466ms/epoch - 23ms/step
Epoch 1163/1500
20/20 - 0s - loss: 0.2488 - categorical_accuracy: 0.9100 - val_loss: 0.2484 - val_categorical_accuracy: 0.9135 - 459ms/epoch - 23ms/step
Epoch 1164/1500
20/20 - 0s - loss: 0.2104 - categorical_accuracy: 0.9281 - val_loss: 0.2472 - val_categorical_accuracy: 0.9132 - 475ms/epoch - 24ms/step
Epoch 1165/1500
20/20 - 0s - loss: 0.2397 - categorical_accuracy: 0.9134 - val_loss: 0.3197 - val_categorical_accuracy: 0.8797 - 465ms/epoch - 23ms/step
Epoch 1166/1500
20/20 - 0s - loss: 0.2403 - categorical_accuracy: 0.9133 - val_loss: 0.2429 - val_categorical_accuracy: 0.9158 - 454ms/epoch - 23ms/step
Epoch 1167/1500
20/20 - 0s - loss: 0.1970 - categorical_accuracy: 0.9344 - val_loss: 0.2283 - val_categorical_accuracy: 0.9238 - 478ms/epoch - 24ms/step
Epoch 1168/1500
20/20 - 0s - loss: 0.2440 - categorical_accuracy: 0.9139 - val_loss: 0.3511 - val_categorical_accuracy: 0.8720 - 468ms/epoch - 23ms/step
Epoch 1169/1500
20/20 - 0s - loss: 0.2614 - categorical_accuracy: 0.9051 - val_loss: 0.2511 - val_categorical_accuracy: 0.9118 - 468ms/epoch - 23ms/step
Epoch 1170/1500
20/20 - 0s - loss: 0.2166 - categorical_accuracy: 0.9259 - val_loss: 0.2438 - val_categorical_accuracy: 0.9144 - 464ms/epoch - 23ms/step
Epoch 1171/1500
20/20 - 0s - loss: 0.2371 - categorical_accuracy: 0.9149 - val_loss: 0.2752 - val_categorical_accuracy: 0.9025 - 458ms/epoch - 23ms/step
Epoch 1172/1500
20/20 - 0s - loss: 0.2258 - categorical_accuracy: 0.9204 - val_loss: 0.2573 - val_categorical_accuracy: 0.9093 - 454ms/epoch - 23ms/step
Epoch 1173/1500
20/20 - 0s - loss: 0.3839 - categorical_accuracy: 0.8901 - val_loss: 0.2833 - val_categorical_accuracy: 0.9008 - 471ms/epoch - 24ms/step
Epoch 1174/1500
20/20 - 0s - loss: 0.2058 - categorical_accuracy: 0.9310 - val_loss: 0.2278 - val_categorical_accuracy: 0.9226 - 459ms/epoch - 23ms/step
Epoch 1175/1500
20/20 - 0s - loss: 0.1931 - categorical_accuracy: 0.9367 - val_loss: 0.2247 - val_categorical_accuracy: 0.9238 - 468ms/epoch - 23ms/step
Epoch 1176/1500
20/20 - 0s - loss: 0.2195 - categorical_accuracy: 0.9247 - val_loss: 0.2859 - val_categorical_accuracy: 0.8975 - 471ms/epoch - 24ms/step
Epoch 1177/1500
20/20 - 0s - loss: 0.2590 - categorical_accuracy: 0.9056 - val_loss: 0.2547 - val_categorical_accuracy: 0.9101 - 458ms/epoch - 23ms/step
Epoch 1178/1500
20/20 - 0s - loss: 0.2068 - categorical_accuracy: 0.9297 - val_loss: 0.2266 - val_categorical_accuracy: 0.9235 - 461ms/epoch - 23ms/step
Epoch 1179/1500
20/20 - 0s - loss: 0.2026 - categorical_accuracy: 0.9316 - val_loss: 0.2629 - val_categorical_accuracy: 0.9034 - 457ms/epoch - 23ms/step
Epoch 1180/1500
20/20 - 0s - loss: 0.2600 - categorical_accuracy: 0.9039 - val_loss: 0.3481 - val_categorical_accuracy: 0.8718 - 455ms/epoch - 23ms/step
Epoch 1181/1500
20/20 - 0s - loss: 0.2345 - categorical_accuracy: 0.9169 - val_loss: 0.2348 - val_categorical_accuracy: 0.9199 - 464ms/epoch - 23ms/step
Epoch 1182/1500
20/20 - 0s - loss: 0.2164 - categorical_accuracy: 0.9249 - val_loss: 0.2769 - val_categorical_accuracy: 0.9005 - 458ms/epoch - 23ms/step
Epoch 1183/1500
20/20 - 0s - loss: 0.2573 - categorical_accuracy: 0.9062 - val_loss: 0.2374 - val_categorical_accuracy: 0.9182 - 465ms/epoch - 23ms/step
Epoch 1184/1500
20/20 - 0s - loss: 0.2022 - categorical_accuracy: 0.9319 - val_loss: 0.2426 - val_categorical_accuracy: 0.9151 - 465ms/epoch - 23ms/step
Epoch 1185/1500
20/20 - 0s - loss: 0.2276 - categorical_accuracy: 0.9195 - val_loss: 0.3011 - val_categorical_accuracy: 0.8942 - 472ms/epoch - 24ms/step
Epoch 1186/1500
20/20 - 0s - loss: 0.2353 - categorical_accuracy: 0.9160 - val_loss: 0.2425 - val_categorical_accuracy: 0.9157 - 456ms/epoch - 23ms/step
Epoch 1187/1500
20/20 - 0s - loss: 0.2009 - categorical_accuracy: 0.9322 - val_loss: 0.2548 - val_categorical_accuracy: 0.9106 - 456ms/epoch - 23ms/step
Epoch 1188/1500
20/20 - 0s - loss: 0.2209 - categorical_accuracy: 0.9229 - val_loss: 0.2501 - val_categorical_accuracy: 0.9123 - 453ms/epoch - 23ms/step
Epoch 1189/1500
20/20 - 0s - loss: 0.2244 - categorical_accuracy: 0.9208 - val_loss: 0.2907 - val_categorical_accuracy: 0.8936 - 455ms/epoch - 23ms/step
Epoch 1190/1500
20/20 - 0s - loss: 0.2924 - categorical_accuracy: 0.8912 - val_loss: 0.2555 - val_categorical_accuracy: 0.9097 - 473ms/epoch - 24ms/step
Epoch 1191/1500
20/20 - 0s - loss: 0.2139 - categorical_accuracy: 0.9255 - val_loss: 0.2241 - val_categorical_accuracy: 0.9237 - 474ms/epoch - 24ms/step
Epoch 1192/1500
20/20 - 0s - loss: 0.1920 - categorical_accuracy: 0.9368 - val_loss: 0.2222 - val_categorical_accuracy: 0.9247 - 468ms/epoch - 23ms/step
Epoch 1193/1500
20/20 - 0s - loss: 0.2255 - categorical_accuracy: 0.9202 - val_loss: 0.2608 - val_categorical_accuracy: 0.9059 - 454ms/epoch - 23ms/step
Epoch 1194/1500
20/20 - 0s - loss: 0.2135 - categorical_accuracy: 0.9258 - val_loss: 0.2355 - val_categorical_accuracy: 0.9180 - 458ms/epoch - 23ms/step
Epoch 1195/1500
20/20 - 0s - loss: 0.2191 - categorical_accuracy: 0.9234 - val_loss: 0.2708 - val_categorical_accuracy: 0.9008 - 469ms/epoch - 23ms/step
Epoch 1196/1500
20/20 - 0s - loss: 0.2425 - categorical_accuracy: 0.9132 - val_loss: 0.2886 - val_categorical_accuracy: 0.8959 - 457ms/epoch - 23ms/step
Epoch 1197/1500
20/20 - 0s - loss: 0.2610 - categorical_accuracy: 0.9045 - val_loss: 0.2406 - val_categorical_accuracy: 0.9157 - 468ms/epoch - 23ms/step
Epoch 1198/1500
20/20 - 0s - loss: 0.2173 - categorical_accuracy: 0.9241 - val_loss: 0.2792 - val_categorical_accuracy: 0.9013 - 468ms/epoch - 23ms/step
Epoch 1199/1500
20/20 - 0s - loss: 0.2125 - categorical_accuracy: 0.9267 - val_loss: 0.2467 - val_categorical_accuracy: 0.9128 - 466ms/epoch - 23ms/step
Epoch 1200/1500
20/20 - 0s - loss: 0.2111 - categorical_accuracy: 0.9271 - val_loss: 0.2282 - val_categorical_accuracy: 0.9217 - 463ms/epoch - 23ms/step
Epoch 1201/1500
20/20 - 0s - loss: 0.1895 - categorical_accuracy: 0.9377 - val_loss: 0.2273 - val_categorical_accuracy: 0.9222 - 481ms/epoch - 24ms/step
Epoch 1202/1500
20/20 - 0s - loss: 0.2782 - categorical_accuracy: 0.8980 - val_loss: 0.3009 - val_categorical_accuracy: 0.8905 - 473ms/epoch - 24ms/step
Epoch 1203/1500
20/20 - 0s - loss: 0.2266 - categorical_accuracy: 0.9197 - val_loss: 0.2450 - val_categorical_accuracy: 0.9159 - 472ms/epoch - 24ms/step
Epoch 1204/1500
20/20 - 0s - loss: 0.2270 - categorical_accuracy: 0.9211 - val_loss: 0.2476 - val_categorical_accuracy: 0.9138 - 474ms/epoch - 24ms/step
Epoch 1205/1500
20/20 - 0s - loss: 0.2118 - categorical_accuracy: 0.9267 - val_loss: 0.2753 - val_categorical_accuracy: 0.8958 - 473ms/epoch - 24ms/step
Epoch 1206/1500
20/20 - 0s - loss: 0.2251 - categorical_accuracy: 0.9203 - val_loss: 0.2416 - val_categorical_accuracy: 0.9157 - 481ms/epoch - 24ms/step
Epoch 1207/1500
20/20 - 0s - loss: 0.2094 - categorical_accuracy: 0.9277 - val_loss: 0.2343 - val_categorical_accuracy: 0.9196 - 469ms/epoch - 23ms/step
Epoch 1208/1500
20/20 - 0s - loss: 0.2044 - categorical_accuracy: 0.9302 - val_loss: 0.2489 - val_categorical_accuracy: 0.9129 - 489ms/epoch - 24ms/step
Epoch 1209/1500
20/20 - 0s - loss: 0.2303 - categorical_accuracy: 0.9186 - val_loss: 0.2429 - val_categorical_accuracy: 0.9157 - 480ms/epoch - 24ms/step
Epoch 1210/1500
20/20 - 0s - loss: 0.2241 - categorical_accuracy: 0.9215 - val_loss: 0.2828 - val_categorical_accuracy: 0.8971 - 486ms/epoch - 24ms/step
Epoch 1211/1500
20/20 - 0s - loss: 0.2524 - categorical_accuracy: 0.9083 - val_loss: 0.2773 - val_categorical_accuracy: 0.9020 - 482ms/epoch - 24ms/step
Epoch 1212/1500
20/20 - 0s - loss: 0.4028 - categorical_accuracy: 0.8840 - val_loss: 0.2254 - val_categorical_accuracy: 0.9235 - 488ms/epoch - 24ms/step
Epoch 1213/1500
20/20 - 0s - loss: 0.1903 - categorical_accuracy: 0.9374 - val_loss: 0.2221 - val_categorical_accuracy: 0.9251 - 480ms/epoch - 24ms/step
Epoch 1214/1500
20/20 - 0s - loss: 0.1882 - categorical_accuracy: 0.9381 - val_loss: 0.2172 - val_categorical_accuracy: 0.9268 - 486ms/epoch - 24ms/step
Epoch 1215/1500
20/20 - 0s - loss: 0.2200 - categorical_accuracy: 0.9218 - val_loss: 0.2876 - val_categorical_accuracy: 0.8975 - 484ms/epoch - 24ms/step
Epoch 1216/1500
20/20 - 0s - loss: 0.2501 - categorical_accuracy: 0.9083 - val_loss: 0.2330 - val_categorical_accuracy: 0.9190 - 484ms/epoch - 24ms/step
Epoch 1217/1500
20/20 - 0s - loss: 0.1944 - categorical_accuracy: 0.9349 - val_loss: 0.2251 - val_categorical_accuracy: 0.9229 - 478ms/epoch - 24ms/step
Epoch 1218/1500
20/20 - 0s - loss: 0.2004 - categorical_accuracy: 0.9319 - val_loss: 0.2476 - val_categorical_accuracy: 0.9126 - 482ms/epoch - 24ms/step
Epoch 1219/1500
20/20 - 0s - loss: 0.2255 - categorical_accuracy: 0.9202 - val_loss: 0.2654 - val_categorical_accuracy: 0.9062 - 488ms/epoch - 24ms/step
Epoch 1220/1500
20/20 - 0s - loss: 0.2080 - categorical_accuracy: 0.9285 - val_loss: 0.2468 - val_categorical_accuracy: 0.9135 - 489ms/epoch - 24ms/step
Epoch 1221/1500
20/20 - 0s - loss: 0.2521 - categorical_accuracy: 0.9078 - val_loss: 0.3716 - val_categorical_accuracy: 0.8636 - 490ms/epoch - 24ms/step
Epoch 1222/1500
20/20 - 0s - loss: 0.2689 - categorical_accuracy: 0.9027 - val_loss: 0.2256 - val_categorical_accuracy: 0.9236 - 488ms/epoch - 24ms/step
Epoch 1223/1500
20/20 - 0s - loss: 0.1895 - categorical_accuracy: 0.9373 - val_loss: 0.2222 - val_categorical_accuracy: 0.9256 - 465ms/epoch - 23ms/step
Epoch 1224/1500
20/20 - 0s - loss: 0.2217 - categorical_accuracy: 0.9228 - val_loss: 0.2419 - val_categorical_accuracy: 0.9163 - 485ms/epoch - 24ms/step
Epoch 1225/1500
20/20 - 0s - loss: 0.2360 - categorical_accuracy: 0.9159 - val_loss: 0.2935 - val_categorical_accuracy: 0.8938 - 471ms/epoch - 24ms/step
Epoch 1226/1500
20/20 - 0s - loss: 0.2156 - categorical_accuracy: 0.9251 - val_loss: 0.2344 - val_categorical_accuracy: 0.9180 - 479ms/epoch - 24ms/step
Epoch 1227/1500
20/20 - 0s - loss: 0.2046 - categorical_accuracy: 0.9299 - val_loss: 0.2500 - val_categorical_accuracy: 0.9100 - 493ms/epoch - 25ms/step
Epoch 1228/1500
20/20 - 0s - loss: 0.2111 - categorical_accuracy: 0.9265 - val_loss: 0.2415 - val_categorical_accuracy: 0.9140 - 488ms/epoch - 24ms/step
Epoch 1229/1500
20/20 - 0s - loss: 0.2152 - categorical_accuracy: 0.9241 - val_loss: 0.2440 - val_categorical_accuracy: 0.9127 - 474ms/epoch - 24ms/step
Epoch 1230/1500
20/20 - 0s - loss: 0.2140 - categorical_accuracy: 0.9245 - val_loss: 0.2398 - val_categorical_accuracy: 0.9160 - 477ms/epoch - 24ms/step
Epoch 1231/1500
20/20 - 0s - loss: 0.3993 - categorical_accuracy: 0.8895 - val_loss: 0.4553 - val_categorical_accuracy: 0.8548 - 478ms/epoch - 24ms/step
Epoch 1232/1500
20/20 - 0s - loss: 1.0223 - categorical_accuracy: 0.8235 - val_loss: 0.2568 - val_categorical_accuracy: 0.9137 - 484ms/epoch - 24ms/step
Epoch 1233/1500
20/20 - 0s - loss: 0.2188 - categorical_accuracy: 0.9294 - val_loss: 0.2392 - val_categorical_accuracy: 0.9197 - 474ms/epoch - 24ms/step
Epoch 1234/1500
20/20 - 0s - loss: 0.2054 - categorical_accuracy: 0.9334 - val_loss: 0.2309 - val_categorical_accuracy: 0.9231 - 483ms/epoch - 24ms/step
Epoch 1235/1500
20/20 - 0s - loss: 0.1979 - categorical_accuracy: 0.9358 - val_loss: 0.2255 - val_categorical_accuracy: 0.9250 - 481ms/epoch - 24ms/step
Epoch 1236/1500
20/20 - 0s - loss: 0.1921 - categorical_accuracy: 0.9378 - val_loss: 0.2213 - val_categorical_accuracy: 0.9266 - 487ms/epoch - 24ms/step
Epoch 1237/1500
20/20 - 0s - loss: 0.1892 - categorical_accuracy: 0.9388 - val_loss: 0.2189 - val_categorical_accuracy: 0.9268 - 472ms/epoch - 24ms/step
Epoch 1238/1500
20/20 - 0s - loss: 0.1917 - categorical_accuracy: 0.9368 - val_loss: 0.2366 - val_categorical_accuracy: 0.9180 - 472ms/epoch - 24ms/step
Epoch 1239/1500
20/20 - 0s - loss: 0.2029 - categorical_accuracy: 0.9313 - val_loss: 0.2427 - val_categorical_accuracy: 0.9147 - 465ms/epoch - 23ms/step
Epoch 1240/1500
20/20 - 0s - loss: 0.2348 - categorical_accuracy: 0.9154 - val_loss: 0.2327 - val_categorical_accuracy: 0.9189 - 471ms/epoch - 24ms/step
Epoch 1241/1500
20/20 - 0s - loss: 0.1866 - categorical_accuracy: 0.9389 - val_loss: 0.2226 - val_categorical_accuracy: 0.9240 - 480ms/epoch - 24ms/step
Epoch 1242/1500
20/20 - 0s - loss: 0.2503 - categorical_accuracy: 0.9104 - val_loss: 0.3232 - val_categorical_accuracy: 0.8829 - 468ms/epoch - 23ms/step
Epoch 1243/1500
20/20 - 0s - loss: 0.2041 - categorical_accuracy: 0.9302 - val_loss: 0.2197 - val_categorical_accuracy: 0.9250 - 482ms/epoch - 24ms/step
Epoch 1244/1500
20/20 - 0s - loss: 0.1931 - categorical_accuracy: 0.9350 - val_loss: 0.2859 - val_categorical_accuracy: 0.8994 - 470ms/epoch - 24ms/step
Epoch 1245/1500
20/20 - 0s - loss: 0.2324 - categorical_accuracy: 0.9166 - val_loss: 0.2408 - val_categorical_accuracy: 0.9158 - 471ms/epoch - 24ms/step
Epoch 1246/1500
20/20 - 0s - loss: 0.2142 - categorical_accuracy: 0.9252 - val_loss: 0.2524 - val_categorical_accuracy: 0.9111 - 484ms/epoch - 24ms/step
Epoch 1247/1500
20/20 - 0s - loss: 0.2082 - categorical_accuracy: 0.9281 - val_loss: 0.2479 - val_categorical_accuracy: 0.9130 - 485ms/epoch - 24ms/step
Epoch 1248/1500
20/20 - 0s - loss: 0.2081 - categorical_accuracy: 0.9279 - val_loss: 0.2399 - val_categorical_accuracy: 0.9166 - 471ms/epoch - 24ms/step
Epoch 1249/1500
20/20 - 0s - loss: 0.2932 - categorical_accuracy: 0.8947 - val_loss: 0.3142 - val_categorical_accuracy: 0.8873 - 486ms/epoch - 24ms/step
Epoch 1250/1500
20/20 - 0s - loss: 0.2080 - categorical_accuracy: 0.9285 - val_loss: 0.2291 - val_categorical_accuracy: 0.9224 - 490ms/epoch - 25ms/step
Epoch 1251/1500
20/20 - 0s - loss: 0.1885 - categorical_accuracy: 0.9370 - val_loss: 0.2227 - val_categorical_accuracy: 0.9243 - 495ms/epoch - 25ms/step
Epoch 1252/1500
20/20 - 0s - loss: 0.2168 - categorical_accuracy: 0.9227 - val_loss: 0.2970 - val_categorical_accuracy: 0.8894 - 486ms/epoch - 24ms/step
Epoch 1253/1500
20/20 - 0s - loss: 0.2510 - categorical_accuracy: 0.9077 - val_loss: 0.2216 - val_categorical_accuracy: 0.9249 - 486ms/epoch - 24ms/step
Epoch 1254/1500
20/20 - 0s - loss: 0.1992 - categorical_accuracy: 0.9312 - val_loss: 0.2399 - val_categorical_accuracy: 0.9165 - 488ms/epoch - 24ms/step
Epoch 1255/1500
20/20 - 0s - loss: 0.1926 - categorical_accuracy: 0.9352 - val_loss: 0.2224 - val_categorical_accuracy: 0.9238 - 485ms/epoch - 24ms/step
Epoch 1256/1500
20/20 - 0s - loss: 0.2296 - categorical_accuracy: 0.9180 - val_loss: 0.3037 - val_categorical_accuracy: 0.8895 - 485ms/epoch - 24ms/step
Epoch 1257/1500
20/20 - 0s - loss: 0.2315 - categorical_accuracy: 0.9170 - val_loss: 0.2255 - val_categorical_accuracy: 0.9218 - 483ms/epoch - 24ms/step
Epoch 1258/1500
20/20 - 0s - loss: 0.1983 - categorical_accuracy: 0.9327 - val_loss: 0.2613 - val_categorical_accuracy: 0.9091 - 469ms/epoch - 23ms/step
Epoch 1259/1500
20/20 - 0s - loss: 0.3489 - categorical_accuracy: 0.8976 - val_loss: 0.2158 - val_categorical_accuracy: 0.9273 - 471ms/epoch - 24ms/step
Epoch 1260/1500
20/20 - 0s - loss: 0.1838 - categorical_accuracy: 0.9392 - val_loss: 0.2213 - val_categorical_accuracy: 0.9238 - 476ms/epoch - 24ms/step
Epoch 1261/1500
20/20 - 0s - loss: 0.1976 - categorical_accuracy: 0.9323 - val_loss: 0.2592 - val_categorical_accuracy: 0.9081 - 484ms/epoch - 24ms/step
Epoch 1262/1500
20/20 - 0s - loss: 0.2315 - categorical_accuracy: 0.9158 - val_loss: 0.2430 - val_categorical_accuracy: 0.9150 - 488ms/epoch - 24ms/step
Epoch 1263/1500
20/20 - 0s - loss: 0.1959 - categorical_accuracy: 0.9329 - val_loss: 0.2270 - val_categorical_accuracy: 0.9215 - 495ms/epoch - 25ms/step
Epoch 1264/1500
20/20 - 0s - loss: 0.2941 - categorical_accuracy: 0.8937 - val_loss: 0.3245 - val_categorical_accuracy: 0.8845 - 493ms/epoch - 25ms/step
Epoch 1265/1500
20/20 - 0s - loss: 0.1967 - categorical_accuracy: 0.9339 - val_loss: 0.2150 - val_categorical_accuracy: 0.9274 - 497ms/epoch - 25ms/step
Epoch 1266/1500
20/20 - 0s - loss: 0.1845 - categorical_accuracy: 0.9385 - val_loss: 0.2269 - val_categorical_accuracy: 0.9213 - 497ms/epoch - 25ms/step
Epoch 1267/1500
20/20 - 1s - loss: 0.2113 - categorical_accuracy: 0.9259 - val_loss: 0.2249 - val_categorical_accuracy: 0.9222 - 502ms/epoch - 25ms/step
Epoch 1268/1500
20/20 - 0s - loss: 0.1968 - categorical_accuracy: 0.9320 - val_loss: 0.2558 - val_categorical_accuracy: 0.9070 - 488ms/epoch - 24ms/step
Epoch 1269/1500
20/20 - 0s - loss: 0.2058 - categorical_accuracy: 0.9277 - val_loss: 0.2441 - val_categorical_accuracy: 0.9123 - 495ms/epoch - 25ms/step
Epoch 1270/1500
20/20 - 0s - loss: 0.2053 - categorical_accuracy: 0.9282 - val_loss: 0.2437 - val_categorical_accuracy: 0.9134 - 477ms/epoch - 24ms/step
Epoch 1271/1500
20/20 - 0s - loss: 0.2201 - categorical_accuracy: 0.9208 - val_loss: 0.2431 - val_categorical_accuracy: 0.9148 - 493ms/epoch - 25ms/step
Epoch 1272/1500
20/20 - 0s - loss: 0.2069 - categorical_accuracy: 0.9274 - val_loss: 0.2408 - val_categorical_accuracy: 0.9168 - 494ms/epoch - 25ms/step
Epoch 1273/1500
20/20 - 0s - loss: 0.2365 - categorical_accuracy: 0.9152 - val_loss: 0.2844 - val_categorical_accuracy: 0.8982 - 494ms/epoch - 25ms/step
Epoch 1274/1500
20/20 - 0s - loss: 0.2315 - categorical_accuracy: 0.9170 - val_loss: 0.2375 - val_categorical_accuracy: 0.9166 - 490ms/epoch - 25ms/step
Epoch 1275/1500
20/20 - 0s - loss: 0.1917 - categorical_accuracy: 0.9353 - val_loss: 0.2372 - val_categorical_accuracy: 0.9165 - 494ms/epoch - 25ms/step
Epoch 1276/1500
20/20 - 0s - loss: 0.2130 - categorical_accuracy: 0.9250 - val_loss: 0.2529 - val_categorical_accuracy: 0.9110 - 490ms/epoch - 25ms/step
Epoch 1277/1500
20/20 - 0s - loss: 0.1872 - categorical_accuracy: 0.9369 - val_loss: 0.2139 - val_categorical_accuracy: 0.9276 - 477ms/epoch - 24ms/step
Epoch 1278/1500
20/20 - 0s - loss: 0.1937 - categorical_accuracy: 0.9345 - val_loss: 0.2831 - val_categorical_accuracy: 0.8992 - 482ms/epoch - 24ms/step
Epoch 1279/1500
20/20 - 0s - loss: 0.2867 - categorical_accuracy: 0.8936 - val_loss: 0.2336 - val_categorical_accuracy: 0.9182 - 471ms/epoch - 24ms/step
Epoch 1280/1500
20/20 - 1s - loss: 0.1878 - categorical_accuracy: 0.9373 - val_loss: 0.2344 - val_categorical_accuracy: 0.9184 - 502ms/epoch - 25ms/step
Epoch 1281/1500
20/20 - 0s - loss: 0.1982 - categorical_accuracy: 0.9320 - val_loss: 0.2299 - val_categorical_accuracy: 0.9212 - 493ms/epoch - 25ms/step
Epoch 1282/1500
20/20 - 0s - loss: 0.2120 - categorical_accuracy: 0.9264 - val_loss: 0.2323 - val_categorical_accuracy: 0.9196 - 485ms/epoch - 24ms/step
Epoch 1283/1500
20/20 - 0s - loss: 0.2049 - categorical_accuracy: 0.9293 - val_loss: 0.2494 - val_categorical_accuracy: 0.9109 - 490ms/epoch - 25ms/step
Epoch 1284/1500
20/20 - 1s - loss: 0.2239 - categorical_accuracy: 0.9199 - val_loss: 0.2467 - val_categorical_accuracy: 0.9105 - 501ms/epoch - 25ms/step
Epoch 1285/1500
20/20 - 1s - loss: 0.4243 - categorical_accuracy: 0.8689 - val_loss: 0.5944 - val_categorical_accuracy: 0.8215 - 512ms/epoch - 26ms/step
Epoch 1286/1500
20/20 - 1s - loss: 0.2735 - categorical_accuracy: 0.9098 - val_loss: 0.2142 - val_categorical_accuracy: 0.9279 - 500ms/epoch - 25ms/step
Epoch 1287/1500
20/20 - 0s - loss: 0.1795 - categorical_accuracy: 0.9418 - val_loss: 0.2115 - val_categorical_accuracy: 0.9292 - 484ms/epoch - 24ms/step
Epoch 1288/1500
20/20 - 0s - loss: 0.1761 - categorical_accuracy: 0.9436 - val_loss: 0.2112 - val_categorical_accuracy: 0.9286 - 492ms/epoch - 25ms/step
Epoch 1289/1500
20/20 - 0s - loss: 0.1835 - categorical_accuracy: 0.9391 - val_loss: 0.2312 - val_categorical_accuracy: 0.9190 - 486ms/epoch - 24ms/step
Epoch 1290/1500
20/20 - 0s - loss: 0.2193 - categorical_accuracy: 0.9215 - val_loss: 0.2760 - val_categorical_accuracy: 0.8993 - 480ms/epoch - 24ms/step
Epoch 1291/1500
20/20 - 0s - loss: 0.2241 - categorical_accuracy: 0.9197 - val_loss: 0.2376 - val_categorical_accuracy: 0.9166 - 489ms/epoch - 24ms/step
Epoch 1292/1500
20/20 - 0s - loss: 0.2054 - categorical_accuracy: 0.9292 - val_loss: 0.2844 - val_categorical_accuracy: 0.8994 - 487ms/epoch - 24ms/step
Epoch 1293/1500
20/20 - 0s - loss: 0.2132 - categorical_accuracy: 0.9241 - val_loss: 0.2520 - val_categorical_accuracy: 0.9109 - 490ms/epoch - 25ms/step
Epoch 1294/1500
20/20 - 0s - loss: 0.2046 - categorical_accuracy: 0.9285 - val_loss: 0.2313 - val_categorical_accuracy: 0.9190 - 480ms/epoch - 24ms/step
Epoch 1295/1500
20/20 - 0s - loss: 0.2078 - categorical_accuracy: 0.9271 - val_loss: 0.2632 - val_categorical_accuracy: 0.9062 - 488ms/epoch - 24ms/step
Epoch 1296/1500
20/20 - 0s - loss: 0.2117 - categorical_accuracy: 0.9252 - val_loss: 0.2267 - val_categorical_accuracy: 0.9212 - 489ms/epoch - 24ms/step
Epoch 1297/1500
20/20 - 0s - loss: 0.2020 - categorical_accuracy: 0.9296 - val_loss: 0.2256 - val_categorical_accuracy: 0.9215 - 487ms/epoch - 24ms/step
Epoch 1298/1500
20/20 - 0s - loss: 0.1994 - categorical_accuracy: 0.9304 - val_loss: 0.2906 - val_categorical_accuracy: 0.8972 - 482ms/epoch - 24ms/step
Epoch 1299/1500
20/20 - 0s - loss: 0.2888 - categorical_accuracy: 0.8912 - val_loss: 0.2563 - val_categorical_accuracy: 0.9089 - 484ms/epoch - 24ms/step
Epoch 1300/1500
20/20 - 0s - loss: 0.1875 - categorical_accuracy: 0.9368 - val_loss: 0.2089 - val_categorical_accuracy: 0.9295 - 482ms/epoch - 24ms/step
Epoch 1301/1500
20/20 - 0s - loss: 0.1779 - categorical_accuracy: 0.9421 - val_loss: 0.2242 - val_categorical_accuracy: 0.9235 - 481ms/epoch - 24ms/step
Epoch 1302/1500
20/20 - 0s - loss: 0.2277 - categorical_accuracy: 0.9183 - val_loss: 0.3045 - val_categorical_accuracy: 0.8897 - 485ms/epoch - 24ms/step
Epoch 1303/1500
20/20 - 0s - loss: 0.2383 - categorical_accuracy: 0.9138 - val_loss: 0.2248 - val_categorical_accuracy: 0.9225 - 498ms/epoch - 25ms/step
Epoch 1304/1500
20/20 - 0s - loss: 0.1808 - categorical_accuracy: 0.9402 - val_loss: 0.2099 - val_categorical_accuracy: 0.9284 - 488ms/epoch - 24ms/step
Epoch 1305/1500
20/20 - 1s - loss: 0.1996 - categorical_accuracy: 0.9313 - val_loss: 0.2827 - val_categorical_accuracy: 0.9003 - 502ms/epoch - 25ms/step
Epoch 1306/1500
20/20 - 0s - loss: 0.2424 - categorical_accuracy: 0.9101 - val_loss: 0.2141 - val_categorical_accuracy: 0.9262 - 488ms/epoch - 24ms/step
Epoch 1307/1500
20/20 - 0s - loss: 0.1762 - categorical_accuracy: 0.9417 - val_loss: 0.2149 - val_categorical_accuracy: 0.9274 - 496ms/epoch - 25ms/step
Epoch 1308/1500
20/20 - 0s - loss: 0.2109 - categorical_accuracy: 0.9261 - val_loss: 0.3014 - val_categorical_accuracy: 0.8918 - 480ms/epoch - 24ms/step
Epoch 1309/1500
20/20 - 0s - loss: 0.2370 - categorical_accuracy: 0.9142 - val_loss: 0.2257 - val_categorical_accuracy: 0.9222 - 486ms/epoch - 24ms/step
Epoch 1310/1500
20/20 - 0s - loss: 0.1958 - categorical_accuracy: 0.9329 - val_loss: 0.2324 - val_categorical_accuracy: 0.9185 - 470ms/epoch - 24ms/step
Epoch 1311/1500
20/20 - 0s - loss: 0.2111 - categorical_accuracy: 0.9248 - val_loss: 0.2341 - val_categorical_accuracy: 0.9176 - 486ms/epoch - 24ms/step
Epoch 1312/1500
20/20 - 0s - loss: 0.1938 - categorical_accuracy: 0.9336 - val_loss: 0.2212 - val_categorical_accuracy: 0.9238 - 484ms/epoch - 24ms/step
Epoch 1313/1500
20/20 - 0s - loss: 0.1909 - categorical_accuracy: 0.9343 - val_loss: 0.2539 - val_categorical_accuracy: 0.9075 - 482ms/epoch - 24ms/step
Epoch 1314/1500
20/20 - 0s - loss: 0.2771 - categorical_accuracy: 0.8986 - val_loss: 0.2643 - val_categorical_accuracy: 0.9113 - 486ms/epoch - 24ms/step
Epoch 1315/1500
20/20 - 1s - loss: 0.1822 - categorical_accuracy: 0.9399 - val_loss: 0.2061 - val_categorical_accuracy: 0.9312 - 505ms/epoch - 25ms/step
Epoch 1316/1500
20/20 - 1s - loss: 0.1767 - categorical_accuracy: 0.9414 - val_loss: 0.2306 - val_categorical_accuracy: 0.9199 - 500ms/epoch - 25ms/step
Epoch 1317/1500
20/20 - 1s - loss: 0.2063 - categorical_accuracy: 0.9282 - val_loss: 0.2344 - val_categorical_accuracy: 0.9170 - 513ms/epoch - 26ms/step
Epoch 1318/1500
20/20 - 1s - loss: 0.2120 - categorical_accuracy: 0.9254 - val_loss: 0.2437 - val_categorical_accuracy: 0.9134 - 520ms/epoch - 26ms/step
Epoch 1319/1500
20/20 - 1s - loss: 0.2325 - categorical_accuracy: 0.9157 - val_loss: 0.2489 - val_categorical_accuracy: 0.9124 - 519ms/epoch - 26ms/step
Epoch 1320/1500
20/20 - 1s - loss: 0.2028 - categorical_accuracy: 0.9296 - val_loss: 0.2392 - val_categorical_accuracy: 0.9155 - 519ms/epoch - 26ms/step
Epoch 1321/1500
20/20 - 1s - loss: 0.1867 - categorical_accuracy: 0.9372 - val_loss: 0.2306 - val_categorical_accuracy: 0.9191 - 505ms/epoch - 25ms/step
Epoch 1322/1500
20/20 - 1s - loss: 0.2260 - categorical_accuracy: 0.9187 - val_loss: 0.2784 - val_categorical_accuracy: 0.9021 - 517ms/epoch - 26ms/step
Epoch 1323/1500
20/20 - 1s - loss: 0.2020 - categorical_accuracy: 0.9292 - val_loss: 0.2242 - val_categorical_accuracy: 0.9218 - 528ms/epoch - 26ms/step
Epoch 1324/1500
20/20 - 1s - loss: 0.1774 - categorical_accuracy: 0.9408 - val_loss: 0.2080 - val_categorical_accuracy: 0.9286 - 549ms/epoch - 27ms/step
Epoch 1325/1500
20/20 - 1s - loss: 0.2324 - categorical_accuracy: 0.9187 - val_loss: 0.4279 - val_categorical_accuracy: 0.8513 - 536ms/epoch - 27ms/step
Epoch 1326/1500
20/20 - 1s - loss: 0.2516 - categorical_accuracy: 0.9103 - val_loss: 0.2067 - val_categorical_accuracy: 0.9307 - 529ms/epoch - 26ms/step
Epoch 1327/1500
20/20 - 1s - loss: 0.1771 - categorical_accuracy: 0.9413 - val_loss: 0.2363 - val_categorical_accuracy: 0.9173 - 519ms/epoch - 26ms/step
Epoch 1328/1500
20/20 - 1s - loss: 0.2182 - categorical_accuracy: 0.9206 - val_loss: 0.2408 - val_categorical_accuracy: 0.9156 - 504ms/epoch - 25ms/step
Epoch 1329/1500
20/20 - 1s - loss: 0.1866 - categorical_accuracy: 0.9366 - val_loss: 0.2229 - val_categorical_accuracy: 0.9224 - 521ms/epoch - 26ms/step
Epoch 1330/1500
20/20 - 1s - loss: 0.1901 - categorical_accuracy: 0.9343 - val_loss: 0.2348 - val_categorical_accuracy: 0.9176 - 518ms/epoch - 26ms/step
Epoch 1331/1500
20/20 - 1s - loss: 0.2026 - categorical_accuracy: 0.9284 - val_loss: 0.2305 - val_categorical_accuracy: 0.9193 - 511ms/epoch - 26ms/step
Epoch 1332/1500
20/20 - 0s - loss: 0.1863 - categorical_accuracy: 0.9368 - val_loss: 0.2344 - val_categorical_accuracy: 0.9193 - 499ms/epoch - 25ms/step
Epoch 1333/1500
20/20 - 1s - loss: 0.3908 - categorical_accuracy: 0.8860 - val_loss: 0.2322 - val_categorical_accuracy: 0.9228 - 502ms/epoch - 25ms/step
Epoch 1334/1500
20/20 - 1s - loss: 0.1746 - categorical_accuracy: 0.9432 - val_loss: 0.2046 - val_categorical_accuracy: 0.9314 - 513ms/epoch - 26ms/step
Epoch 1335/1500
20/20 - 1s - loss: 0.1681 - categorical_accuracy: 0.9458 - val_loss: 0.2036 - val_categorical_accuracy: 0.9314 - 522ms/epoch - 26ms/step
Epoch 1336/1500
20/20 - 0s - loss: 0.1887 - categorical_accuracy: 0.9352 - val_loss: 0.2176 - val_categorical_accuracy: 0.9248 - 499ms/epoch - 25ms/step
Epoch 1337/1500
20/20 - 0s - loss: 0.2047 - categorical_accuracy: 0.9282 - val_loss: 0.2255 - val_categorical_accuracy: 0.9222 - 495ms/epoch - 25ms/step
Epoch 1338/1500
20/20 - 0s - loss: 0.1987 - categorical_accuracy: 0.9313 - val_loss: 0.2704 - val_categorical_accuracy: 0.9028 - 485ms/epoch - 24ms/step
Epoch 1339/1500
20/20 - 0s - loss: 0.2810 - categorical_accuracy: 0.8969 - val_loss: 0.2247 - val_categorical_accuracy: 0.9217 - 483ms/epoch - 24ms/step
Epoch 1340/1500
20/20 - 0s - loss: 0.1858 - categorical_accuracy: 0.9369 - val_loss: 0.2036 - val_categorical_accuracy: 0.9319 - 468ms/epoch - 23ms/step
Epoch 1341/1500
20/20 - 0s - loss: 0.1835 - categorical_accuracy: 0.9380 - val_loss: 0.2344 - val_categorical_accuracy: 0.9182 - 473ms/epoch - 24ms/step
Epoch 1342/1500
20/20 - 0s - loss: 0.2093 - categorical_accuracy: 0.9262 - val_loss: 0.2280 - val_categorical_accuracy: 0.9198 - 472ms/epoch - 24ms/step
Epoch 1343/1500
20/20 - 0s - loss: 0.1759 - categorical_accuracy: 0.9412 - val_loss: 0.2058 - val_categorical_accuracy: 0.9300 - 481ms/epoch - 24ms/step
Epoch 1344/1500
20/20 - 0s - loss: 0.1812 - categorical_accuracy: 0.9386 - val_loss: 0.2221 - val_categorical_accuracy: 0.9229 - 472ms/epoch - 24ms/step
Epoch 1345/1500
20/20 - 0s - loss: 0.1979 - categorical_accuracy: 0.9315 - val_loss: 0.2767 - val_categorical_accuracy: 0.8963 - 476ms/epoch - 24ms/step
Epoch 1346/1500
20/20 - 0s - loss: 0.2625 - categorical_accuracy: 0.9015 - val_loss: 0.2671 - val_categorical_accuracy: 0.9042 - 480ms/epoch - 24ms/step
Epoch 1347/1500
20/20 - 0s - loss: 0.1843 - categorical_accuracy: 0.9375 - val_loss: 0.2309 - val_categorical_accuracy: 0.9192 - 479ms/epoch - 24ms/step
Epoch 1348/1500
20/20 - 0s - loss: 0.2077 - categorical_accuracy: 0.9269 - val_loss: 0.2726 - val_categorical_accuracy: 0.9027 - 473ms/epoch - 24ms/step
Epoch 1349/1500
20/20 - 0s - loss: 0.1982 - categorical_accuracy: 0.9309 - val_loss: 0.2086 - val_categorical_accuracy: 0.9289 - 486ms/epoch - 24ms/step
Epoch 1350/1500
20/20 - 0s - loss: 0.1711 - categorical_accuracy: 0.9439 - val_loss: 0.2157 - val_categorical_accuracy: 0.9254 - 489ms/epoch - 24ms/step
Epoch 1351/1500
20/20 - 0s - loss: 0.1874 - categorical_accuracy: 0.9360 - val_loss: 0.2467 - val_categorical_accuracy: 0.9131 - 486ms/epoch - 24ms/step
Epoch 1352/1500
20/20 - 0s - loss: 0.8793 - categorical_accuracy: 0.8168 - val_loss: 0.2563 - val_categorical_accuracy: 0.9109 - 486ms/epoch - 24ms/step
Epoch 1353/1500
20/20 - 0s - loss: 0.1967 - categorical_accuracy: 0.9361 - val_loss: 0.2181 - val_categorical_accuracy: 0.9273 - 487ms/epoch - 24ms/step
Epoch 1354/1500
20/20 - 0s - loss: 0.1821 - categorical_accuracy: 0.9417 - val_loss: 0.2112 - val_categorical_accuracy: 0.9297 - 472ms/epoch - 24ms/step
Epoch 1355/1500
20/20 - 0s - loss: 0.1758 - categorical_accuracy: 0.9437 - val_loss: 0.2103 - val_categorical_accuracy: 0.9288 - 466ms/epoch - 23ms/step
Epoch 1356/1500
20/20 - 0s - loss: 0.1717 - categorical_accuracy: 0.9452 - val_loss: 0.2041 - val_categorical_accuracy: 0.9318 - 494ms/epoch - 25ms/step
Epoch 1357/1500
20/20 - 0s - loss: 0.1689 - categorical_accuracy: 0.9457 - val_loss: 0.2030 - val_categorical_accuracy: 0.9317 - 467ms/epoch - 23ms/step
Epoch 1358/1500
20/20 - 0s - loss: 0.1708 - categorical_accuracy: 0.9446 - val_loss: 0.2114 - val_categorical_accuracy: 0.9275 - 484ms/epoch - 24ms/step
Epoch 1359/1500
20/20 - 1s - loss: 0.2009 - categorical_accuracy: 0.9303 - val_loss: 0.3113 - val_categorical_accuracy: 0.8895 - 763ms/epoch - 38ms/step
Epoch 1360/1500
20/20 - 0s - loss: 0.2454 - categorical_accuracy: 0.9108 - val_loss: 0.2355 - val_categorical_accuracy: 0.9170 - 477ms/epoch - 24ms/step
Epoch 1361/1500
20/20 - 0s - loss: 0.1815 - categorical_accuracy: 0.9391 - val_loss: 0.2095 - val_categorical_accuracy: 0.9291 - 486ms/epoch - 24ms/step
Epoch 1362/1500
20/20 - 0s - loss: 0.1721 - categorical_accuracy: 0.9431 - val_loss: 0.2036 - val_categorical_accuracy: 0.9314 - 481ms/epoch - 24ms/step
Epoch 1363/1500
20/20 - 0s - loss: 0.1980 - categorical_accuracy: 0.9314 - val_loss: 0.3183 - val_categorical_accuracy: 0.8826 - 473ms/epoch - 24ms/step
Epoch 1364/1500
20/20 - 0s - loss: 0.2476 - categorical_accuracy: 0.9105 - val_loss: 0.2097 - val_categorical_accuracy: 0.9283 - 471ms/epoch - 24ms/step
Epoch 1365/1500
20/20 - 0s - loss: 0.1734 - categorical_accuracy: 0.9423 - val_loss: 0.2203 - val_categorical_accuracy: 0.9240 - 480ms/epoch - 24ms/step
Epoch 1366/1500
20/20 - 0s - loss: 0.1944 - categorical_accuracy: 0.9321 - val_loss: 0.2413 - val_categorical_accuracy: 0.9155 - 473ms/epoch - 24ms/step
Epoch 1367/1500
20/20 - 0s - loss: 0.2280 - categorical_accuracy: 0.9180 - val_loss: 0.2624 - val_categorical_accuracy: 0.9075 - 475ms/epoch - 24ms/step
Epoch 1368/1500
20/20 - 0s - loss: 0.1974 - categorical_accuracy: 0.9316 - val_loss: 0.2058 - val_categorical_accuracy: 0.9296 - 473ms/epoch - 24ms/step
Epoch 1369/1500
20/20 - 0s - loss: 0.1715 - categorical_accuracy: 0.9431 - val_loss: 0.2219 - val_categorical_accuracy: 0.9225 - 472ms/epoch - 24ms/step
Epoch 1370/1500
20/20 - 0s - loss: 0.1752 - categorical_accuracy: 0.9412 - val_loss: 0.2408 - val_categorical_accuracy: 0.9163 - 474ms/epoch - 24ms/step
Epoch 1371/1500
20/20 - 0s - loss: 0.2164 - categorical_accuracy: 0.9219 - val_loss: 0.2908 - val_categorical_accuracy: 0.8979 - 467ms/epoch - 23ms/step
Epoch 1372/1500
20/20 - 0s - loss: 0.2149 - categorical_accuracy: 0.9222 - val_loss: 0.2356 - val_categorical_accuracy: 0.9176 - 466ms/epoch - 23ms/step
Epoch 1373/1500
20/20 - 0s - loss: 0.1806 - categorical_accuracy: 0.9390 - val_loss: 0.2334 - val_categorical_accuracy: 0.9180 - 471ms/epoch - 24ms/step
Epoch 1374/1500
20/20 - 0s - loss: 0.2308 - categorical_accuracy: 0.9169 - val_loss: 0.2969 - val_categorical_accuracy: 0.8950 - 458ms/epoch - 23ms/step
Epoch 1375/1500
20/20 - 0s - loss: 0.2304 - categorical_accuracy: 0.9177 - val_loss: 0.2018 - val_categorical_accuracy: 0.9320 - 471ms/epoch - 24ms/step
Epoch 1376/1500
20/20 - 0s - loss: 0.1662 - categorical_accuracy: 0.9457 - val_loss: 0.2027 - val_categorical_accuracy: 0.9319 - 472ms/epoch - 24ms/step
Epoch 1377/1500
20/20 - 0s - loss: 0.1837 - categorical_accuracy: 0.9374 - val_loss: 0.2500 - val_categorical_accuracy: 0.9074 - 467ms/epoch - 23ms/step
Epoch 1378/1500
20/20 - 0s - loss: 0.2244 - categorical_accuracy: 0.9180 - val_loss: 0.2222 - val_categorical_accuracy: 0.9227 - 478ms/epoch - 24ms/step
Epoch 1379/1500
20/20 - 0s - loss: 0.1763 - categorical_accuracy: 0.9403 - val_loss: 0.2023 - val_categorical_accuracy: 0.9316 - 468ms/epoch - 23ms/step
Epoch 1380/1500
20/20 - 0s - loss: 0.1779 - categorical_accuracy: 0.9399 - val_loss: 0.2490 - val_categorical_accuracy: 0.9130 - 482ms/epoch - 24ms/step
Epoch 1381/1500
20/20 - 0s - loss: 0.1951 - categorical_accuracy: 0.9321 - val_loss: 0.2290 - val_categorical_accuracy: 0.9199 - 468ms/epoch - 23ms/step
Epoch 1382/1500
20/20 - 0s - loss: 0.2512 - categorical_accuracy: 0.9088 - val_loss: 0.2998 - val_categorical_accuracy: 0.8929 - 482ms/epoch - 24ms/step
Epoch 1383/1500
20/20 - 0s - loss: 0.1960 - categorical_accuracy: 0.9327 - val_loss: 0.2007 - val_categorical_accuracy: 0.9331 - 472ms/epoch - 24ms/step
Epoch 1384/1500
20/20 - 0s - loss: 0.1801 - categorical_accuracy: 0.9397 - val_loss: 0.2493 - val_categorical_accuracy: 0.9119 - 470ms/epoch - 24ms/step
Epoch 1385/1500
20/20 - 0s - loss: 0.1994 - categorical_accuracy: 0.9300 - val_loss: 0.2576 - val_categorical_accuracy: 0.9090 - 470ms/epoch - 24ms/step
Epoch 1386/1500
20/20 - 0s - loss: 0.2215 - categorical_accuracy: 0.9194 - val_loss: 0.2076 - val_categorical_accuracy: 0.9283 - 469ms/epoch - 23ms/step
Epoch 1387/1500
20/20 - 0s - loss: 0.1681 - categorical_accuracy: 0.9443 - val_loss: 0.2386 - val_categorical_accuracy: 0.9165 - 467ms/epoch - 23ms/step
Epoch 1388/1500
20/20 - 0s - loss: 0.1954 - categorical_accuracy: 0.9313 - val_loss: 0.2225 - val_categorical_accuracy: 0.9229 - 467ms/epoch - 23ms/step
Epoch 1389/1500
20/20 - 0s - loss: 0.1866 - categorical_accuracy: 0.9356 - val_loss: 0.2289 - val_categorical_accuracy: 0.9199 - 474ms/epoch - 24ms/step
Epoch 1390/1500
20/20 - 0s - loss: 0.1877 - categorical_accuracy: 0.9353 - val_loss: 0.2594 - val_categorical_accuracy: 0.9088 - 465ms/epoch - 23ms/step
Epoch 1391/1500
20/20 - 0s - loss: 0.2369 - categorical_accuracy: 0.9123 - val_loss: 0.2203 - val_categorical_accuracy: 0.9233 - 475ms/epoch - 24ms/step
Epoch 1392/1500
20/20 - 0s - loss: 0.1835 - categorical_accuracy: 0.9376 - val_loss: 0.2251 - val_categorical_accuracy: 0.9222 - 469ms/epoch - 23ms/step
Epoch 1393/1500
20/20 - 0s - loss: 0.1796 - categorical_accuracy: 0.9396 - val_loss: 0.2285 - val_categorical_accuracy: 0.9201 - 478ms/epoch - 24ms/step
Epoch 1394/1500
20/20 - 0s - loss: 0.1941 - categorical_accuracy: 0.9324 - val_loss: 0.2139 - val_categorical_accuracy: 0.9257 - 468ms/epoch - 23ms/step
Epoch 1395/1500
20/20 - 0s - loss: 0.1840 - categorical_accuracy: 0.9364 - val_loss: 0.2269 - val_categorical_accuracy: 0.9200 - 465ms/epoch - 23ms/step
Epoch 1396/1500
20/20 - 0s - loss: 0.1962 - categorical_accuracy: 0.9311 - val_loss: 0.2031 - val_categorical_accuracy: 0.9313 - 474ms/epoch - 24ms/step
Epoch 1397/1500
20/20 - 0s - loss: 0.1667 - categorical_accuracy: 0.9446 - val_loss: 0.2124 - val_categorical_accuracy: 0.9263 - 476ms/epoch - 24ms/step
Epoch 1398/1500
20/20 - 0s - loss: 0.2459 - categorical_accuracy: 0.9112 - val_loss: 0.2585 - val_categorical_accuracy: 0.9084 - 464ms/epoch - 23ms/step
Epoch 1399/1500
20/20 - 0s - loss: 0.1864 - categorical_accuracy: 0.9367 - val_loss: 0.2106 - val_categorical_accuracy: 0.9282 - 465ms/epoch - 23ms/step
Epoch 1400/1500
20/20 - 0s - loss: 0.5249 - categorical_accuracy: 0.8889 - val_loss: 1.1385 - val_categorical_accuracy: 0.7364 - 467ms/epoch - 23ms/step
Epoch 1401/1500
20/20 - 0s - loss: 0.3657 - categorical_accuracy: 0.9050 - val_loss: 0.2112 - val_categorical_accuracy: 0.9296 - 469ms/epoch - 23ms/step
Epoch 1402/1500
20/20 - 0s - loss: 0.1734 - categorical_accuracy: 0.9445 - val_loss: 0.2035 - val_categorical_accuracy: 0.9324 - 465ms/epoch - 23ms/step
Epoch 1403/1500
20/20 - 0s - loss: 0.1675 - categorical_accuracy: 0.9464 - val_loss: 0.2026 - val_categorical_accuracy: 0.9324 - 466ms/epoch - 23ms/step
Epoch 1404/1500
20/20 - 0s - loss: 0.1643 - categorical_accuracy: 0.9472 - val_loss: 0.1979 - val_categorical_accuracy: 0.9337 - 460ms/epoch - 23ms/step
Epoch 1405/1500
20/20 - 0s - loss: 0.1645 - categorical_accuracy: 0.9470 - val_loss: 0.2127 - val_categorical_accuracy: 0.9263 - 468ms/epoch - 23ms/step
Epoch 1406/1500
20/20 - 0s - loss: 0.1689 - categorical_accuracy: 0.9437 - val_loss: 0.2035 - val_categorical_accuracy: 0.9306 - 474ms/epoch - 24ms/step
Epoch 1407/1500
20/20 - 0s - loss: 0.1862 - categorical_accuracy: 0.9358 - val_loss: 0.2888 - val_categorical_accuracy: 0.8986 - 470ms/epoch - 24ms/step
Epoch 1408/1500
20/20 - 0s - loss: 0.2744 - categorical_accuracy: 0.8974 - val_loss: 0.2296 - val_categorical_accuracy: 0.9193 - 488ms/epoch - 24ms/step
Epoch 1409/1500
20/20 - 0s - loss: 0.1658 - categorical_accuracy: 0.9456 - val_loss: 0.1993 - val_categorical_accuracy: 0.9325 - 456ms/epoch - 23ms/step
Epoch 1410/1500
20/20 - 0s - loss: 0.1669 - categorical_accuracy: 0.9450 - val_loss: 0.2073 - val_categorical_accuracy: 0.9288 - 458ms/epoch - 23ms/step
Epoch 1411/1500
20/20 - 0s - loss: 0.1893 - categorical_accuracy: 0.9346 - val_loss: 0.2396 - val_categorical_accuracy: 0.9145 - 467ms/epoch - 23ms/step
Epoch 1412/1500
20/20 - 0s - loss: 0.1906 - categorical_accuracy: 0.9335 - val_loss: 0.2220 - val_categorical_accuracy: 0.9230 - 497ms/epoch - 25ms/step
Epoch 1413/1500
20/20 - 1s - loss: 0.1770 - categorical_accuracy: 0.9400 - val_loss: 0.2243 - val_categorical_accuracy: 0.9224 - 506ms/epoch - 25ms/step
Epoch 1414/1500
20/20 - 0s - loss: 0.1831 - categorical_accuracy: 0.9373 - val_loss: 0.2487 - val_categorical_accuracy: 0.9117 - 497ms/epoch - 25ms/step
Epoch 1415/1500
20/20 - 0s - loss: 0.2704 - categorical_accuracy: 0.9019 - val_loss: 0.2389 - val_categorical_accuracy: 0.9166 - 498ms/epoch - 25ms/step
Epoch 1416/1500
20/20 - 0s - loss: 0.1746 - categorical_accuracy: 0.9412 - val_loss: 0.2332 - val_categorical_accuracy: 0.9170 - 488ms/epoch - 24ms/step
Epoch 1417/1500
20/20 - 0s - loss: 0.2586 - categorical_accuracy: 0.9034 - val_loss: 0.2167 - val_categorical_accuracy: 0.9251 - 490ms/epoch - 25ms/step
Epoch 1418/1500
20/20 - 0s - loss: 0.1639 - categorical_accuracy: 0.9466 - val_loss: 0.1979 - val_categorical_accuracy: 0.9339 - 490ms/epoch - 25ms/step
Epoch 1419/1500
20/20 - 0s - loss: 0.1600 - categorical_accuracy: 0.9484 - val_loss: 0.1974 - val_categorical_accuracy: 0.9337 - 471ms/epoch - 24ms/step
Epoch 1420/1500
20/20 - 0s - loss: 0.1622 - categorical_accuracy: 0.9472 - val_loss: 0.2086 - val_categorical_accuracy: 0.9279 - 492ms/epoch - 25ms/step
Epoch 1421/1500
20/20 - 0s - loss: 0.2145 - categorical_accuracy: 0.9236 - val_loss: 0.3499 - val_categorical_accuracy: 0.8748 - 490ms/epoch - 25ms/step
Epoch 1422/1500
20/20 - 1s - loss: 0.2128 - categorical_accuracy: 0.9238 - val_loss: 0.2192 - val_categorical_accuracy: 0.9240 - 503ms/epoch - 25ms/step
Epoch 1423/1500
20/20 - 1s - loss: 0.1925 - categorical_accuracy: 0.9330 - val_loss: 0.2451 - val_categorical_accuracy: 0.9110 - 501ms/epoch - 25ms/step
Epoch 1424/1500
20/20 - 1s - loss: 0.2371 - categorical_accuracy: 0.9128 - val_loss: 0.2064 - val_categorical_accuracy: 0.9297 - 502ms/epoch - 25ms/step
Epoch 1425/1500
20/20 - 0s - loss: 0.1618 - categorical_accuracy: 0.9472 - val_loss: 0.1958 - val_categorical_accuracy: 0.9348 - 488ms/epoch - 24ms/step
Epoch 1426/1500
20/20 - 0s - loss: 0.1665 - categorical_accuracy: 0.9453 - val_loss: 0.2199 - val_categorical_accuracy: 0.9234 - 488ms/epoch - 24ms/step
Epoch 1427/1500
20/20 - 0s - loss: 0.1766 - categorical_accuracy: 0.9402 - val_loss: 0.2181 - val_categorical_accuracy: 0.9235 - 485ms/epoch - 24ms/step
Epoch 1428/1500
20/20 - 1s - loss: 0.2028 - categorical_accuracy: 0.9274 - val_loss: 0.2357 - val_categorical_accuracy: 0.9158 - 515ms/epoch - 26ms/step
Epoch 1429/1500
20/20 - 1s - loss: 0.1751 - categorical_accuracy: 0.9402 - val_loss: 0.1946 - val_categorical_accuracy: 0.9353 - 510ms/epoch - 26ms/step
Epoch 1430/1500
20/20 - 1s - loss: 0.1587 - categorical_accuracy: 0.9486 - val_loss: 0.1952 - val_categorical_accuracy: 0.9344 - 510ms/epoch - 26ms/step
Epoch 1431/1500
20/20 - 1s - loss: 0.1992 - categorical_accuracy: 0.9303 - val_loss: 0.3397 - val_categorical_accuracy: 0.8779 - 510ms/epoch - 26ms/step
Epoch 1432/1500
20/20 - 1s - loss: 0.2804 - categorical_accuracy: 0.9002 - val_loss: 0.2108 - val_categorical_accuracy: 0.9269 - 500ms/epoch - 25ms/step
Epoch 1433/1500
20/20 - 0s - loss: 0.1810 - categorical_accuracy: 0.9377 - val_loss: 0.2177 - val_categorical_accuracy: 0.9242 - 493ms/epoch - 25ms/step
Epoch 1434/1500
20/20 - 0s - loss: 0.1710 - categorical_accuracy: 0.9426 - val_loss: 0.2150 - val_categorical_accuracy: 0.9247 - 495ms/epoch - 25ms/step
Epoch 1435/1500
20/20 - 0s - loss: 0.1616 - categorical_accuracy: 0.9468 - val_loss: 0.2221 - val_categorical_accuracy: 0.9227 - 497ms/epoch - 25ms/step
Epoch 1436/1500
20/20 - 1s - loss: 0.1860 - categorical_accuracy: 0.9357 - val_loss: 0.2749 - val_categorical_accuracy: 0.9042 - 504ms/epoch - 25ms/step
Epoch 1437/1500
20/20 - 0s - loss: 0.1968 - categorical_accuracy: 0.9310 - val_loss: 0.2086 - val_categorical_accuracy: 0.9283 - 481ms/epoch - 24ms/step
Epoch 1438/1500
20/20 - 0s - loss: 0.1876 - categorical_accuracy: 0.9358 - val_loss: 0.2597 - val_categorical_accuracy: 0.9092 - 496ms/epoch - 25ms/step
Epoch 1439/1500
20/20 - 0s - loss: 0.1959 - categorical_accuracy: 0.9309 - val_loss: 0.3245 - val_categorical_accuracy: 0.8878 - 497ms/epoch - 25ms/step
Epoch 1440/1500
20/20 - 0s - loss: 0.2638 - categorical_accuracy: 0.9048 - val_loss: 0.1989 - val_categorical_accuracy: 0.9320 - 490ms/epoch - 25ms/step
Epoch 1441/1500
20/20 - 0s - loss: 0.1585 - categorical_accuracy: 0.9486 - val_loss: 0.2001 - val_categorical_accuracy: 0.9325 - 496ms/epoch - 25ms/step
Epoch 1442/1500
20/20 - 0s - loss: 0.1632 - categorical_accuracy: 0.9464 - val_loss: 0.2294 - val_categorical_accuracy: 0.9200 - 488ms/epoch - 24ms/step
Epoch 1443/1500
20/20 - 0s - loss: 0.2029 - categorical_accuracy: 0.9282 - val_loss: 0.2239 - val_categorical_accuracy: 0.9216 - 499ms/epoch - 25ms/step
Epoch 1444/1500
20/20 - 0s - loss: 0.1839 - categorical_accuracy: 0.9367 - val_loss: 0.2086 - val_categorical_accuracy: 0.9278 - 487ms/epoch - 24ms/step
Epoch 1445/1500
20/20 - 0s - loss: 0.1572 - categorical_accuracy: 0.9491 - val_loss: 0.1933 - val_categorical_accuracy: 0.9349 - 470ms/epoch - 24ms/step
Epoch 1446/1500
20/20 - 0s - loss: 0.1816 - categorical_accuracy: 0.9375 - val_loss: 0.2468 - val_categorical_accuracy: 0.9135 - 484ms/epoch - 24ms/step
Epoch 1447/1500
20/20 - 0s - loss: 0.2330 - categorical_accuracy: 0.9148 - val_loss: 0.2670 - val_categorical_accuracy: 0.9052 - 488ms/epoch - 24ms/step
Epoch 1448/1500
20/20 - 0s - loss: 0.2092 - categorical_accuracy: 0.9241 - val_loss: 0.2043 - val_categorical_accuracy: 0.9294 - 485ms/epoch - 24ms/step
Epoch 1449/1500
20/20 - 0s - loss: 0.1721 - categorical_accuracy: 0.9418 - val_loss: 0.2262 - val_categorical_accuracy: 0.9215 - 483ms/epoch - 24ms/step
Epoch 1450/1500
20/20 - 0s - loss: 0.1898 - categorical_accuracy: 0.9342 - val_loss: 0.2227 - val_categorical_accuracy: 0.9233 - 494ms/epoch - 25ms/step
Epoch 1451/1500
20/20 - 0s - loss: 0.1712 - categorical_accuracy: 0.9417 - val_loss: 0.2212 - val_categorical_accuracy: 0.9232 - 476ms/epoch - 24ms/step
Epoch 1452/1500
20/20 - 0s - loss: 0.1723 - categorical_accuracy: 0.9412 - val_loss: 0.2509 - val_categorical_accuracy: 0.9124 - 494ms/epoch - 25ms/step
Epoch 1453/1500
20/20 - 0s - loss: 0.1880 - categorical_accuracy: 0.9338 - val_loss: 0.3020 - val_categorical_accuracy: 0.8946 - 472ms/epoch - 24ms/step
Epoch 1454/1500
20/20 - 0s - loss: 0.2342 - categorical_accuracy: 0.9149 - val_loss: 0.2050 - val_categorical_accuracy: 0.9284 - 484ms/epoch - 24ms/step
Epoch 1455/1500
20/20 - 0s - loss: 0.1571 - categorical_accuracy: 0.9487 - val_loss: 0.1973 - val_categorical_accuracy: 0.9334 - 472ms/epoch - 24ms/step
Epoch 1456/1500
20/20 - 0s - loss: 0.8434 - categorical_accuracy: 0.8423 - val_loss: 0.2382 - val_categorical_accuracy: 0.9189 - 483ms/epoch - 24ms/step
Epoch 1457/1500
20/20 - 0s - loss: 0.1832 - categorical_accuracy: 0.9412 - val_loss: 0.2071 - val_categorical_accuracy: 0.9317 - 483ms/epoch - 24ms/step
Epoch 1458/1500
20/20 - 0s - loss: 0.1688 - categorical_accuracy: 0.9469 - val_loss: 0.1999 - val_categorical_accuracy: 0.9333 - 473ms/epoch - 24ms/step
Epoch 1459/1500
20/20 - 0s - loss: 0.1626 - categorical_accuracy: 0.9484 - val_loss: 0.1961 - val_categorical_accuracy: 0.9345 - 489ms/epoch - 24ms/step
Epoch 1460/1500
20/20 - 0s - loss: 0.1588 - categorical_accuracy: 0.9495 - val_loss: 0.1954 - val_categorical_accuracy: 0.9350 - 489ms/epoch - 24ms/step
Epoch 1461/1500
20/20 - 0s - loss: 0.1574 - categorical_accuracy: 0.9493 - val_loss: 0.1928 - val_categorical_accuracy: 0.9354 - 492ms/epoch - 25ms/step
Epoch 1462/1500
20/20 - 0s - loss: 0.1549 - categorical_accuracy: 0.9503 - val_loss: 0.1901 - val_categorical_accuracy: 0.9361 - 486ms/epoch - 24ms/step
Epoch 1463/1500
20/20 - 0s - loss: 0.1634 - categorical_accuracy: 0.9451 - val_loss: 0.2171 - val_categorical_accuracy: 0.9246 - 472ms/epoch - 24ms/step
Epoch 1464/1500
20/20 - 1s - loss: 0.1724 - categorical_accuracy: 0.9412 - val_loss: 0.1965 - val_categorical_accuracy: 0.9329 - 502ms/epoch - 25ms/step
Epoch 1465/1500
20/20 - 1s - loss: 0.1824 - categorical_accuracy: 0.9370 - val_loss: 0.3267 - val_categorical_accuracy: 0.8876 - 502ms/epoch - 25ms/step
Epoch 1466/1500
20/20 - 1s - loss: 0.2413 - categorical_accuracy: 0.9103 - val_loss: 0.2075 - val_categorical_accuracy: 0.9279 - 504ms/epoch - 25ms/step
Epoch 1467/1500
20/20 - 1s - loss: 0.1697 - categorical_accuracy: 0.9428 - val_loss: 0.2331 - val_categorical_accuracy: 0.9182 - 516ms/epoch - 26ms/step
Epoch 1468/1500
20/20 - 1s - loss: 0.2656 - categorical_accuracy: 0.9032 - val_loss: 0.2328 - val_categorical_accuracy: 0.9192 - 504ms/epoch - 25ms/step
Epoch 1469/1500
20/20 - 1s - loss: 0.1616 - categorical_accuracy: 0.9468 - val_loss: 0.1928 - val_categorical_accuracy: 0.9347 - 504ms/epoch - 25ms/step
Epoch 1470/1500
20/20 - 1s - loss: 0.1569 - categorical_accuracy: 0.9485 - val_loss: 0.2172 - val_categorical_accuracy: 0.9245 - 504ms/epoch - 25ms/step
Epoch 1471/1500
20/20 - 0s - loss: 0.1780 - categorical_accuracy: 0.9389 - val_loss: 0.2023 - val_categorical_accuracy: 0.9301 - 498ms/epoch - 25ms/step
Epoch 1472/1500
20/20 - 1s - loss: 0.1607 - categorical_accuracy: 0.9460 - val_loss: 0.2256 - val_categorical_accuracy: 0.9213 - 508ms/epoch - 25ms/step
Epoch 1473/1500
20/20 - 0s - loss: 0.1686 - categorical_accuracy: 0.9435 - val_loss: 0.2107 - val_categorical_accuracy: 0.9268 - 492ms/epoch - 25ms/step
Epoch 1474/1500
20/20 - 0s - loss: 0.1927 - categorical_accuracy: 0.9322 - val_loss: 0.2910 - val_categorical_accuracy: 0.8977 - 484ms/epoch - 24ms/step
Epoch 1475/1500
20/20 - 0s - loss: 0.2689 - categorical_accuracy: 0.9048 - val_loss: 0.1944 - val_categorical_accuracy: 0.9336 - 490ms/epoch - 24ms/step
Epoch 1476/1500
20/20 - 0s - loss: 0.1668 - categorical_accuracy: 0.9443 - val_loss: 0.2237 - val_categorical_accuracy: 0.9223 - 495ms/epoch - 25ms/step
Epoch 1477/1500
20/20 - 0s - loss: 0.1710 - categorical_accuracy: 0.9421 - val_loss: 0.2462 - val_categorical_accuracy: 0.9139 - 475ms/epoch - 24ms/step
Epoch 1478/1500
20/20 - 0s - loss: 0.1905 - categorical_accuracy: 0.9329 - val_loss: 0.2318 - val_categorical_accuracy: 0.9186 - 485ms/epoch - 24ms/step
Epoch 1479/1500
20/20 - 0s - loss: 0.1836 - categorical_accuracy: 0.9360 - val_loss: 0.2116 - val_categorical_accuracy: 0.9261 - 486ms/epoch - 24ms/step
Epoch 1480/1500
20/20 - 0s - loss: 0.1563 - categorical_accuracy: 0.9484 - val_loss: 0.2096 - val_categorical_accuracy: 0.9277 - 472ms/epoch - 24ms/step
Epoch 1481/1500
20/20 - 0s - loss: 0.1663 - categorical_accuracy: 0.9437 - val_loss: 0.2465 - val_categorical_accuracy: 0.9144 - 482ms/epoch - 24ms/step
Epoch 1482/1500
20/20 - 0s - loss: 0.1868 - categorical_accuracy: 0.9343 - val_loss: 0.2532 - val_categorical_accuracy: 0.9114 - 486ms/epoch - 24ms/step
Epoch 1483/1500
20/20 - 0s - loss: 0.2691 - categorical_accuracy: 0.9016 - val_loss: 0.2351 - val_categorical_accuracy: 0.9170 - 483ms/epoch - 24ms/step
Epoch 1484/1500
20/20 - 0s - loss: 0.1605 - categorical_accuracy: 0.9472 - val_loss: 0.1906 - val_categorical_accuracy: 0.9364 - 489ms/epoch - 24ms/step
Epoch 1485/1500
20/20 - 0s - loss: 0.1515 - categorical_accuracy: 0.9512 - val_loss: 0.1896 - val_categorical_accuracy: 0.9370 - 486ms/epoch - 24ms/step
Epoch 1486/1500
20/20 - 0s - loss: 0.1925 - categorical_accuracy: 0.9323 - val_loss: 0.2750 - val_categorical_accuracy: 0.8975 - 487ms/epoch - 24ms/step
Epoch 1487/1500
20/20 - 0s - loss: 0.2529 - categorical_accuracy: 0.9062 - val_loss: 0.2035 - val_categorical_accuracy: 0.9311 - 467ms/epoch - 23ms/step
Epoch 1488/1500
20/20 - 0s - loss: 0.1528 - categorical_accuracy: 0.9506 - val_loss: 0.1931 - val_categorical_accuracy: 0.9350 - 488ms/epoch - 24ms/step
Epoch 1489/1500
20/20 - 0s - loss: 0.1575 - categorical_accuracy: 0.9473 - val_loss: 0.1947 - val_categorical_accuracy: 0.9335 - 470ms/epoch - 24ms/step
Epoch 1490/1500
20/20 - 0s - loss: 0.1607 - categorical_accuracy: 0.9465 - val_loss: 0.2432 - val_categorical_accuracy: 0.9130 - 472ms/epoch - 24ms/step
Epoch 1491/1500
20/20 - 0s - loss: 0.1973 - categorical_accuracy: 0.9303 - val_loss: 0.2186 - val_categorical_accuracy: 0.9237 - 474ms/epoch - 24ms/step
Epoch 1492/1500
20/20 - 0s - loss: 0.1666 - categorical_accuracy: 0.9437 - val_loss: 0.1926 - val_categorical_accuracy: 0.9348 - 487ms/epoch - 24ms/step
Epoch 1493/1500
20/20 - 0s - loss: 0.1687 - categorical_accuracy: 0.9426 - val_loss: 0.2249 - val_categorical_accuracy: 0.9213 - 480ms/epoch - 24ms/step
Epoch 1494/1500
20/20 - 0s - loss: 0.2024 - categorical_accuracy: 0.9282 - val_loss: 0.2256 - val_categorical_accuracy: 0.9212 - 472ms/epoch - 24ms/step
Epoch 1495/1500
20/20 - 0s - loss: 0.1575 - categorical_accuracy: 0.9483 - val_loss: 0.1882 - val_categorical_accuracy: 0.9364 - 487ms/epoch - 24ms/step
Epoch 1496/1500
20/20 - 0s - loss: 0.2490 - categorical_accuracy: 0.9245 - val_loss: 3.3997 - val_categorical_accuracy: 0.7035 - 486ms/epoch - 24ms/step
Epoch 1497/1500
20/20 - 1s - loss: 0.7729 - categorical_accuracy: 0.8477 - val_loss: 0.2114 - val_categorical_accuracy: 0.9290 - 504ms/epoch - 25ms/step
Epoch 1498/1500
20/20 - 1s - loss: 0.1701 - categorical_accuracy: 0.9454 - val_loss: 0.1995 - val_categorical_accuracy: 0.9341 - 506ms/epoch - 25ms/step
Epoch 1499/1500
20/20 - 1s - loss: 0.1618 - categorical_accuracy: 0.9488 - val_loss: 0.1953 - val_categorical_accuracy: 0.9348 - 517ms/epoch - 26ms/step
Epoch 1500/1500
20/20 - 0s - loss: 0.1572 - categorical_accuracy: 0.9499 - val_loss: 0.1911 - val_categorical_accuracy: 0.9361 - 496ms/epoch - 25ms/step
processing fold # 2 
Epoch 1/1500
20/20 - 1s - loss: 2.0751 - categorical_accuracy: 0.1323 - val_loss: 2.0701 - val_categorical_accuracy: 0.1533 - 1s/epoch - 66ms/step
Epoch 2/1500
20/20 - 0s - loss: 2.0663 - categorical_accuracy: 0.2029 - val_loss: 2.0619 - val_categorical_accuracy: 0.2670 - 494ms/epoch - 25ms/step
Epoch 3/1500
20/20 - 0s - loss: 2.0584 - categorical_accuracy: 0.2883 - val_loss: 2.0542 - val_categorical_accuracy: 0.2987 - 481ms/epoch - 24ms/step
Epoch 4/1500
20/20 - 0s - loss: 2.0508 - categorical_accuracy: 0.3027 - val_loss: 2.0468 - val_categorical_accuracy: 0.3045 - 481ms/epoch - 24ms/step
Epoch 5/1500
20/20 - 0s - loss: 2.0433 - categorical_accuracy: 0.3112 - val_loss: 2.0391 - val_categorical_accuracy: 0.3255 - 481ms/epoch - 24ms/step
Epoch 6/1500
20/20 - 0s - loss: 2.0354 - categorical_accuracy: 0.3288 - val_loss: 2.0312 - val_categorical_accuracy: 0.3281 - 483ms/epoch - 24ms/step
Epoch 7/1500
20/20 - 1s - loss: 2.0274 - categorical_accuracy: 0.3277 - val_loss: 2.0231 - val_categorical_accuracy: 0.3272 - 501ms/epoch - 25ms/step
Epoch 8/1500
20/20 - 1s - loss: 2.0190 - categorical_accuracy: 0.3292 - val_loss: 2.0145 - val_categorical_accuracy: 0.3295 - 502ms/epoch - 25ms/step
Epoch 9/1500
20/20 - 0s - loss: 2.0102 - categorical_accuracy: 0.3308 - val_loss: 2.0054 - val_categorical_accuracy: 0.3302 - 484ms/epoch - 24ms/step
Epoch 10/1500
20/20 - 1s - loss: 2.0008 - categorical_accuracy: 0.3325 - val_loss: 1.9957 - val_categorical_accuracy: 0.3317 - 502ms/epoch - 25ms/step
Epoch 11/1500
20/20 - 1s - loss: 1.9907 - categorical_accuracy: 0.3327 - val_loss: 1.9853 - val_categorical_accuracy: 0.3315 - 507ms/epoch - 25ms/step
Epoch 12/1500
20/20 - 1s - loss: 1.9800 - categorical_accuracy: 0.3317 - val_loss: 1.9744 - val_categorical_accuracy: 0.3326 - 500ms/epoch - 25ms/step
Epoch 13/1500
20/20 - 0s - loss: 1.9687 - categorical_accuracy: 0.3327 - val_loss: 1.9627 - val_categorical_accuracy: 0.3314 - 490ms/epoch - 25ms/step
Epoch 14/1500
20/20 - 0s - loss: 1.9567 - categorical_accuracy: 0.3316 - val_loss: 1.9504 - val_categorical_accuracy: 0.3302 - 489ms/epoch - 24ms/step
Epoch 15/1500
20/20 - 0s - loss: 1.9440 - categorical_accuracy: 0.3301 - val_loss: 1.9375 - val_categorical_accuracy: 0.3310 - 495ms/epoch - 25ms/step
Epoch 16/1500
20/20 - 0s - loss: 1.9308 - categorical_accuracy: 0.3306 - val_loss: 1.9239 - val_categorical_accuracy: 0.3298 - 480ms/epoch - 24ms/step
Epoch 17/1500
20/20 - 0s - loss: 1.9169 - categorical_accuracy: 0.3300 - val_loss: 1.9098 - val_categorical_accuracy: 0.3308 - 473ms/epoch - 24ms/step
Epoch 18/1500
20/20 - 0s - loss: 1.9024 - categorical_accuracy: 0.3313 - val_loss: 1.8950 - val_categorical_accuracy: 0.3323 - 489ms/epoch - 24ms/step
Epoch 19/1500
20/20 - 0s - loss: 1.8873 - categorical_accuracy: 0.3325 - val_loss: 1.8798 - val_categorical_accuracy: 0.3332 - 476ms/epoch - 24ms/step
Epoch 20/1500
20/20 - 0s - loss: 1.8719 - categorical_accuracy: 0.3335 - val_loss: 1.8642 - val_categorical_accuracy: 0.3340 - 473ms/epoch - 24ms/step
Epoch 21/1500
20/20 - 0s - loss: 1.8561 - categorical_accuracy: 0.3346 - val_loss: 1.8483 - val_categorical_accuracy: 0.3320 - 469ms/epoch - 23ms/step
Epoch 22/1500
20/20 - 0s - loss: 1.8400 - categorical_accuracy: 0.3356 - val_loss: 1.8321 - val_categorical_accuracy: 0.3360 - 474ms/epoch - 24ms/step
Epoch 23/1500
20/20 - 0s - loss: 1.8237 - categorical_accuracy: 0.3381 - val_loss: 1.8157 - val_categorical_accuracy: 0.3392 - 470ms/epoch - 24ms/step
Epoch 24/1500
20/20 - 0s - loss: 1.8071 - categorical_accuracy: 0.3482 - val_loss: 1.7991 - val_categorical_accuracy: 0.3577 - 471ms/epoch - 24ms/step
Epoch 25/1500
20/20 - 0s - loss: 1.7905 - categorical_accuracy: 0.3609 - val_loss: 1.7825 - val_categorical_accuracy: 0.3630 - 483ms/epoch - 24ms/step
Epoch 26/1500
20/20 - 0s - loss: 1.7737 - categorical_accuracy: 0.3664 - val_loss: 1.7657 - val_categorical_accuracy: 0.3699 - 467ms/epoch - 23ms/step
Epoch 27/1500
20/20 - 0s - loss: 1.7570 - categorical_accuracy: 0.3735 - val_loss: 1.7490 - val_categorical_accuracy: 0.3762 - 473ms/epoch - 24ms/step
Epoch 28/1500
20/20 - 0s - loss: 1.7402 - categorical_accuracy: 0.3805 - val_loss: 1.7323 - val_categorical_accuracy: 0.3825 - 470ms/epoch - 24ms/step
Epoch 29/1500
20/20 - 0s - loss: 1.7236 - categorical_accuracy: 0.3855 - val_loss: 1.7156 - val_categorical_accuracy: 0.3840 - 473ms/epoch - 24ms/step
Epoch 30/1500
20/20 - 0s - loss: 1.7069 - categorical_accuracy: 0.3895 - val_loss: 1.6990 - val_categorical_accuracy: 0.3865 - 475ms/epoch - 24ms/step
Epoch 31/1500
20/20 - 1s - loss: 1.6903 - categorical_accuracy: 0.3941 - val_loss: 1.6825 - val_categorical_accuracy: 0.3970 - 513ms/epoch - 26ms/step
Epoch 32/1500
20/20 - 0s - loss: 1.6738 - categorical_accuracy: 0.3995 - val_loss: 1.6661 - val_categorical_accuracy: 0.3980 - 496ms/epoch - 25ms/step
Epoch 33/1500
20/20 - 0s - loss: 1.6574 - categorical_accuracy: 0.4031 - val_loss: 1.6498 - val_categorical_accuracy: 0.4035 - 499ms/epoch - 25ms/step
Epoch 34/1500
20/20 - 1s - loss: 1.6413 - categorical_accuracy: 0.4103 - val_loss: 1.6337 - val_categorical_accuracy: 0.4119 - 500ms/epoch - 25ms/step
Epoch 35/1500
20/20 - 1s - loss: 1.6253 - categorical_accuracy: 0.4156 - val_loss: 1.6180 - val_categorical_accuracy: 0.4161 - 522ms/epoch - 26ms/step
Epoch 36/1500
20/20 - 0s - loss: 1.6095 - categorical_accuracy: 0.4191 - val_loss: 1.6023 - val_categorical_accuracy: 0.4174 - 486ms/epoch - 24ms/step
Epoch 37/1500
20/20 - 0s - loss: 1.5941 - categorical_accuracy: 0.4223 - val_loss: 1.5870 - val_categorical_accuracy: 0.4220 - 488ms/epoch - 24ms/step
Epoch 38/1500
20/20 - 0s - loss: 1.5789 - categorical_accuracy: 0.4265 - val_loss: 1.5721 - val_categorical_accuracy: 0.4247 - 489ms/epoch - 24ms/step
Epoch 39/1500
20/20 - 1s - loss: 1.5641 - categorical_accuracy: 0.4297 - val_loss: 1.5575 - val_categorical_accuracy: 0.4293 - 502ms/epoch - 25ms/step
Epoch 40/1500
20/20 - 1s - loss: 1.5497 - categorical_accuracy: 0.4346 - val_loss: 1.5433 - val_categorical_accuracy: 0.4358 - 514ms/epoch - 26ms/step
Epoch 41/1500
20/20 - 1s - loss: 1.5356 - categorical_accuracy: 0.4396 - val_loss: 1.5294 - val_categorical_accuracy: 0.4395 - 506ms/epoch - 25ms/step
Epoch 42/1500
20/20 - 1s - loss: 1.5219 - categorical_accuracy: 0.4449 - val_loss: 1.5159 - val_categorical_accuracy: 0.4467 - 504ms/epoch - 25ms/step
Epoch 43/1500
20/20 - 1s - loss: 1.5086 - categorical_accuracy: 0.4512 - val_loss: 1.5028 - val_categorical_accuracy: 0.4512 - 518ms/epoch - 26ms/step
Epoch 44/1500
20/20 - 1s - loss: 1.4956 - categorical_accuracy: 0.4555 - val_loss: 1.4906 - val_categorical_accuracy: 0.4533 - 520ms/epoch - 26ms/step
Epoch 45/1500
20/20 - 1s - loss: 1.4832 - categorical_accuracy: 0.4584 - val_loss: 1.4779 - val_categorical_accuracy: 0.4601 - 504ms/epoch - 25ms/step
Epoch 46/1500
20/20 - 1s - loss: 1.4710 - categorical_accuracy: 0.4630 - val_loss: 1.4660 - val_categorical_accuracy: 0.4637 - 502ms/epoch - 25ms/step
Epoch 47/1500
20/20 - 0s - loss: 1.4593 - categorical_accuracy: 0.4673 - val_loss: 1.4545 - val_categorical_accuracy: 0.4666 - 490ms/epoch - 25ms/step
Epoch 48/1500
20/20 - 0s - loss: 1.4480 - categorical_accuracy: 0.4722 - val_loss: 1.4433 - val_categorical_accuracy: 0.4706 - 488ms/epoch - 24ms/step
Epoch 49/1500
20/20 - 0s - loss: 1.4369 - categorical_accuracy: 0.4755 - val_loss: 1.4325 - val_categorical_accuracy: 0.4732 - 481ms/epoch - 24ms/step
Epoch 50/1500
20/20 - 0s - loss: 1.4262 - categorical_accuracy: 0.4781 - val_loss: 1.4220 - val_categorical_accuracy: 0.4768 - 480ms/epoch - 24ms/step
Epoch 51/1500
20/20 - 0s - loss: 1.4157 - categorical_accuracy: 0.4810 - val_loss: 1.4116 - val_categorical_accuracy: 0.4811 - 477ms/epoch - 24ms/step
Epoch 52/1500
20/20 - 0s - loss: 1.4055 - categorical_accuracy: 0.4846 - val_loss: 1.4016 - val_categorical_accuracy: 0.4848 - 474ms/epoch - 24ms/step
Epoch 53/1500
20/20 - 0s - loss: 1.3955 - categorical_accuracy: 0.4890 - val_loss: 1.3919 - val_categorical_accuracy: 0.4906 - 472ms/epoch - 24ms/step
Epoch 54/1500
20/20 - 0s - loss: 1.3857 - categorical_accuracy: 0.4937 - val_loss: 1.3820 - val_categorical_accuracy: 0.4942 - 488ms/epoch - 24ms/step
Epoch 55/1500
20/20 - 0s - loss: 1.3762 - categorical_accuracy: 0.4975 - val_loss: 1.3725 - val_categorical_accuracy: 0.4978 - 488ms/epoch - 24ms/step
Epoch 56/1500
20/20 - 0s - loss: 1.3668 - categorical_accuracy: 0.5024 - val_loss: 1.3632 - val_categorical_accuracy: 0.5028 - 484ms/epoch - 24ms/step
Epoch 57/1500
20/20 - 0s - loss: 1.3575 - categorical_accuracy: 0.5064 - val_loss: 1.3542 - val_categorical_accuracy: 0.5067 - 496ms/epoch - 25ms/step
Epoch 58/1500
20/20 - 1s - loss: 1.3483 - categorical_accuracy: 0.5110 - val_loss: 1.3455 - val_categorical_accuracy: 0.5119 - 510ms/epoch - 25ms/step
Epoch 59/1500
20/20 - 1s - loss: 1.3395 - categorical_accuracy: 0.5157 - val_loss: 1.3363 - val_categorical_accuracy: 0.5149 - 505ms/epoch - 25ms/step
Epoch 60/1500
20/20 - 1s - loss: 1.3307 - categorical_accuracy: 0.5197 - val_loss: 1.3276 - val_categorical_accuracy: 0.5196 - 778ms/epoch - 39ms/step
Epoch 61/1500
20/20 - 0s - loss: 1.3220 - categorical_accuracy: 0.5229 - val_loss: 1.3192 - val_categorical_accuracy: 0.5221 - 480ms/epoch - 24ms/step
Epoch 62/1500
20/20 - 0s - loss: 1.3135 - categorical_accuracy: 0.5264 - val_loss: 1.3107 - val_categorical_accuracy: 0.5260 - 489ms/epoch - 24ms/step
Epoch 63/1500
20/20 - 0s - loss: 1.3052 - categorical_accuracy: 0.5296 - val_loss: 1.3026 - val_categorical_accuracy: 0.5275 - 484ms/epoch - 24ms/step
Epoch 64/1500
20/20 - 0s - loss: 1.2970 - categorical_accuracy: 0.5319 - val_loss: 1.2944 - val_categorical_accuracy: 0.5321 - 474ms/epoch - 24ms/step
Epoch 65/1500
20/20 - 0s - loss: 1.2889 - categorical_accuracy: 0.5354 - val_loss: 1.2866 - val_categorical_accuracy: 0.5363 - 472ms/epoch - 24ms/step
Epoch 66/1500
20/20 - 0s - loss: 1.2810 - categorical_accuracy: 0.5378 - val_loss: 1.2786 - val_categorical_accuracy: 0.5368 - 483ms/epoch - 24ms/step
Epoch 67/1500
20/20 - 0s - loss: 1.2731 - categorical_accuracy: 0.5398 - val_loss: 1.2711 - val_categorical_accuracy: 0.5407 - 467ms/epoch - 23ms/step
Epoch 68/1500
20/20 - 0s - loss: 1.2653 - categorical_accuracy: 0.5431 - val_loss: 1.2635 - val_categorical_accuracy: 0.5425 - 479ms/epoch - 24ms/step
Epoch 69/1500
20/20 - 0s - loss: 1.2577 - categorical_accuracy: 0.5454 - val_loss: 1.2561 - val_categorical_accuracy: 0.5453 - 482ms/epoch - 24ms/step
Epoch 70/1500
20/20 - 0s - loss: 1.2500 - categorical_accuracy: 0.5481 - val_loss: 1.2485 - val_categorical_accuracy: 0.5475 - 470ms/epoch - 24ms/step
Epoch 71/1500
20/20 - 0s - loss: 1.2426 - categorical_accuracy: 0.5503 - val_loss: 1.2412 - val_categorical_accuracy: 0.5511 - 466ms/epoch - 23ms/step
Epoch 72/1500
20/20 - 0s - loss: 1.2355 - categorical_accuracy: 0.5535 - val_loss: 1.2343 - val_categorical_accuracy: 0.5495 - 466ms/epoch - 23ms/step
Epoch 73/1500
20/20 - 0s - loss: 1.2281 - categorical_accuracy: 0.5563 - val_loss: 1.2269 - val_categorical_accuracy: 0.5546 - 482ms/epoch - 24ms/step
Epoch 74/1500
20/20 - 0s - loss: 1.2209 - categorical_accuracy: 0.5591 - val_loss: 1.2198 - val_categorical_accuracy: 0.5582 - 464ms/epoch - 23ms/step
Epoch 75/1500
20/20 - 0s - loss: 1.2139 - categorical_accuracy: 0.5617 - val_loss: 1.2133 - val_categorical_accuracy: 0.5609 - 480ms/epoch - 24ms/step
Epoch 76/1500
20/20 - 0s - loss: 1.2068 - categorical_accuracy: 0.5648 - val_loss: 1.2065 - val_categorical_accuracy: 0.5645 - 460ms/epoch - 23ms/step
Epoch 77/1500
20/20 - 0s - loss: 1.2000 - categorical_accuracy: 0.5676 - val_loss: 1.1993 - val_categorical_accuracy: 0.5666 - 471ms/epoch - 24ms/step
Epoch 78/1500
20/20 - 0s - loss: 1.1931 - categorical_accuracy: 0.5707 - val_loss: 1.1927 - val_categorical_accuracy: 0.5685 - 470ms/epoch - 24ms/step
Epoch 79/1500
20/20 - 0s - loss: 1.1866 - categorical_accuracy: 0.5731 - val_loss: 1.1857 - val_categorical_accuracy: 0.5712 - 467ms/epoch - 23ms/step
Epoch 80/1500
20/20 - 0s - loss: 1.1795 - categorical_accuracy: 0.5759 - val_loss: 1.1792 - val_categorical_accuracy: 0.5744 - 471ms/epoch - 24ms/step
Epoch 81/1500
20/20 - 0s - loss: 1.1730 - categorical_accuracy: 0.5786 - val_loss: 1.1725 - val_categorical_accuracy: 0.5764 - 471ms/epoch - 24ms/step
Epoch 82/1500
20/20 - 0s - loss: 1.1664 - categorical_accuracy: 0.5806 - val_loss: 1.1664 - val_categorical_accuracy: 0.5780 - 468ms/epoch - 23ms/step
Epoch 83/1500
20/20 - 0s - loss: 1.1599 - categorical_accuracy: 0.5828 - val_loss: 1.1623 - val_categorical_accuracy: 0.5808 - 482ms/epoch - 24ms/step
Epoch 84/1500
20/20 - 0s - loss: 1.1539 - categorical_accuracy: 0.5856 - val_loss: 1.1542 - val_categorical_accuracy: 0.5829 - 472ms/epoch - 24ms/step
Epoch 85/1500
20/20 - 0s - loss: 1.1471 - categorical_accuracy: 0.5877 - val_loss: 1.1479 - val_categorical_accuracy: 0.5859 - 472ms/epoch - 24ms/step
Epoch 86/1500
20/20 - 0s - loss: 1.1406 - categorical_accuracy: 0.5902 - val_loss: 1.1416 - val_categorical_accuracy: 0.5880 - 482ms/epoch - 24ms/step
Epoch 87/1500
20/20 - 0s - loss: 1.1345 - categorical_accuracy: 0.5927 - val_loss: 1.1350 - val_categorical_accuracy: 0.5895 - 490ms/epoch - 25ms/step
Epoch 88/1500
20/20 - 0s - loss: 1.1282 - categorical_accuracy: 0.5954 - val_loss: 1.1311 - val_categorical_accuracy: 0.5925 - 499ms/epoch - 25ms/step
Epoch 89/1500
20/20 - 0s - loss: 1.1222 - categorical_accuracy: 0.5977 - val_loss: 1.1226 - val_categorical_accuracy: 0.5946 - 494ms/epoch - 25ms/step
Epoch 90/1500
20/20 - 0s - loss: 1.1163 - categorical_accuracy: 0.5998 - val_loss: 1.1165 - val_categorical_accuracy: 0.5973 - 485ms/epoch - 24ms/step
Epoch 91/1500
20/20 - 0s - loss: 1.1098 - categorical_accuracy: 0.6025 - val_loss: 1.1127 - val_categorical_accuracy: 0.6000 - 475ms/epoch - 24ms/step
Epoch 92/1500
20/20 - 0s - loss: 1.1041 - categorical_accuracy: 0.6049 - val_loss: 1.1048 - val_categorical_accuracy: 0.6026 - 497ms/epoch - 25ms/step
Epoch 93/1500
20/20 - 0s - loss: 1.0978 - categorical_accuracy: 0.6066 - val_loss: 1.0989 - val_categorical_accuracy: 0.6050 - 492ms/epoch - 25ms/step
Epoch 94/1500
20/20 - 0s - loss: 1.0922 - categorical_accuracy: 0.6099 - val_loss: 1.0937 - val_categorical_accuracy: 0.6068 - 480ms/epoch - 24ms/step
Epoch 95/1500
20/20 - 0s - loss: 1.0870 - categorical_accuracy: 0.6112 - val_loss: 1.0886 - val_categorical_accuracy: 0.6082 - 484ms/epoch - 24ms/step
Epoch 96/1500
20/20 - 0s - loss: 1.0809 - categorical_accuracy: 0.6131 - val_loss: 1.0824 - val_categorical_accuracy: 0.6095 - 490ms/epoch - 25ms/step
Epoch 97/1500
20/20 - 0s - loss: 1.0753 - categorical_accuracy: 0.6149 - val_loss: 1.0778 - val_categorical_accuracy: 0.6134 - 496ms/epoch - 25ms/step
Epoch 98/1500
20/20 - 0s - loss: 1.0733 - categorical_accuracy: 0.6158 - val_loss: 1.0803 - val_categorical_accuracy: 0.6103 - 489ms/epoch - 24ms/step
Epoch 99/1500
20/20 - 0s - loss: 1.0714 - categorical_accuracy: 0.6156 - val_loss: 1.0699 - val_categorical_accuracy: 0.6142 - 478ms/epoch - 24ms/step
Epoch 100/1500
20/20 - 0s - loss: 1.0629 - categorical_accuracy: 0.6180 - val_loss: 1.0763 - val_categorical_accuracy: 0.6134 - 473ms/epoch - 24ms/step
Epoch 101/1500
20/20 - 0s - loss: 1.0694 - categorical_accuracy: 0.6162 - val_loss: 1.0708 - val_categorical_accuracy: 0.6152 - 478ms/epoch - 24ms/step
Epoch 102/1500
20/20 - 0s - loss: 1.0581 - categorical_accuracy: 0.6205 - val_loss: 1.0560 - val_categorical_accuracy: 0.6199 - 482ms/epoch - 24ms/step
Epoch 103/1500
20/20 - 0s - loss: 1.0464 - categorical_accuracy: 0.6238 - val_loss: 1.0457 - val_categorical_accuracy: 0.6233 - 487ms/epoch - 24ms/step
Epoch 104/1500
20/20 - 0s - loss: 1.0372 - categorical_accuracy: 0.6268 - val_loss: 1.0404 - val_categorical_accuracy: 0.6259 - 478ms/epoch - 24ms/step
Epoch 105/1500
20/20 - 1s - loss: 1.0491 - categorical_accuracy: 0.6222 - val_loss: 1.0837 - val_categorical_accuracy: 0.6101 - 512ms/epoch - 26ms/step
Epoch 106/1500
20/20 - 0s - loss: 1.0645 - categorical_accuracy: 0.6167 - val_loss: 1.0407 - val_categorical_accuracy: 0.6233 - 499ms/epoch - 25ms/step
Epoch 107/1500
20/20 - 0s - loss: 1.0295 - categorical_accuracy: 0.6291 - val_loss: 1.0341 - val_categorical_accuracy: 0.6278 - 489ms/epoch - 24ms/step
Epoch 108/1500
20/20 - 0s - loss: 1.0254 - categorical_accuracy: 0.6308 - val_loss: 1.0340 - val_categorical_accuracy: 0.6274 - 499ms/epoch - 25ms/step
Epoch 109/1500
20/20 - 1s - loss: 1.0453 - categorical_accuracy: 0.6232 - val_loss: 1.0151 - val_categorical_accuracy: 0.6330 - 512ms/epoch - 26ms/step
Epoch 110/1500
20/20 - 0s - loss: 1.0068 - categorical_accuracy: 0.6363 - val_loss: 1.0108 - val_categorical_accuracy: 0.6340 - 499ms/epoch - 25ms/step
Epoch 111/1500
20/20 - 0s - loss: 1.0040 - categorical_accuracy: 0.6380 - val_loss: 1.0217 - val_categorical_accuracy: 0.6302 - 491ms/epoch - 25ms/step
Epoch 112/1500
20/20 - 0s - loss: 1.0391 - categorical_accuracy: 0.6243 - val_loss: 1.0650 - val_categorical_accuracy: 0.6132 - 485ms/epoch - 24ms/step
Epoch 113/1500
20/20 - 0s - loss: 1.0121 - categorical_accuracy: 0.6344 - val_loss: 0.9968 - val_categorical_accuracy: 0.6396 - 498ms/epoch - 25ms/step
Epoch 114/1500
20/20 - 1s - loss: 0.9877 - categorical_accuracy: 0.6435 - val_loss: 0.9896 - val_categorical_accuracy: 0.6418 - 502ms/epoch - 25ms/step
Epoch 115/1500
20/20 - 0s - loss: 0.9922 - categorical_accuracy: 0.6407 - val_loss: 1.0488 - val_categorical_accuracy: 0.6224 - 481ms/epoch - 24ms/step
Epoch 116/1500
20/20 - 0s - loss: 1.0313 - categorical_accuracy: 0.6272 - val_loss: 0.9852 - val_categorical_accuracy: 0.6429 - 497ms/epoch - 25ms/step
Epoch 117/1500
20/20 - 0s - loss: 0.9740 - categorical_accuracy: 0.6479 - val_loss: 0.9786 - val_categorical_accuracy: 0.6438 - 468ms/epoch - 23ms/step
Epoch 118/1500
20/20 - 0s - loss: 0.9754 - categorical_accuracy: 0.6467 - val_loss: 0.9940 - val_categorical_accuracy: 0.6385 - 481ms/epoch - 24ms/step
Epoch 119/1500
20/20 - 0s - loss: 0.9962 - categorical_accuracy: 0.6391 - val_loss: 0.9747 - val_categorical_accuracy: 0.6450 - 474ms/epoch - 24ms/step
Epoch 120/1500
20/20 - 0s - loss: 0.9611 - categorical_accuracy: 0.6516 - val_loss: 0.9627 - val_categorical_accuracy: 0.6508 - 486ms/epoch - 24ms/step
Epoch 121/1500
20/20 - 0s - loss: 0.9581 - categorical_accuracy: 0.6522 - val_loss: 0.9653 - val_categorical_accuracy: 0.6489 - 486ms/epoch - 24ms/step
Epoch 122/1500
20/20 - 0s - loss: 0.9782 - categorical_accuracy: 0.6438 - val_loss: 1.0123 - val_categorical_accuracy: 0.6333 - 483ms/epoch - 24ms/step
Epoch 123/1500
20/20 - 0s - loss: 0.9862 - categorical_accuracy: 0.6426 - val_loss: 0.9845 - val_categorical_accuracy: 0.6413 - 481ms/epoch - 24ms/step
Epoch 124/1500
20/20 - 0s - loss: 0.9575 - categorical_accuracy: 0.6517 - val_loss: 0.9527 - val_categorical_accuracy: 0.6532 - 497ms/epoch - 25ms/step
Epoch 125/1500
20/20 - 1s - loss: 0.9400 - categorical_accuracy: 0.6581 - val_loss: 0.9415 - val_categorical_accuracy: 0.6553 - 511ms/epoch - 26ms/step
Epoch 126/1500
20/20 - 1s - loss: 0.9424 - categorical_accuracy: 0.6566 - val_loss: 0.9843 - val_categorical_accuracy: 0.6412 - 512ms/epoch - 26ms/step
Epoch 127/1500
20/20 - 1s - loss: 0.9776 - categorical_accuracy: 0.6442 - val_loss: 0.9474 - val_categorical_accuracy: 0.6548 - 519ms/epoch - 26ms/step
Epoch 128/1500
20/20 - 1s - loss: 0.9298 - categorical_accuracy: 0.6606 - val_loss: 0.9299 - val_categorical_accuracy: 0.6612 - 508ms/epoch - 25ms/step
Epoch 129/1500
20/20 - 1s - loss: 0.9298 - categorical_accuracy: 0.6601 - val_loss: 0.9430 - val_categorical_accuracy: 0.6534 - 512ms/epoch - 26ms/step
Epoch 130/1500
20/20 - 1s - loss: 0.9483 - categorical_accuracy: 0.6538 - val_loss: 0.9540 - val_categorical_accuracy: 0.6518 - 504ms/epoch - 25ms/step
Epoch 131/1500
20/20 - 1s - loss: 0.9273 - categorical_accuracy: 0.6605 - val_loss: 0.9173 - val_categorical_accuracy: 0.6656 - 510ms/epoch - 26ms/step
Epoch 132/1500
20/20 - 0s - loss: 0.9096 - categorical_accuracy: 0.6673 - val_loss: 0.9125 - val_categorical_accuracy: 0.6668 - 493ms/epoch - 25ms/step
Epoch 133/1500
20/20 - 1s - loss: 0.9279 - categorical_accuracy: 0.6607 - val_loss: 0.9420 - val_categorical_accuracy: 0.6542 - 504ms/epoch - 25ms/step
Epoch 134/1500
20/20 - 1s - loss: 0.9286 - categorical_accuracy: 0.6613 - val_loss: 0.9052 - val_categorical_accuracy: 0.6678 - 500ms/epoch - 25ms/step
Epoch 135/1500
20/20 - 0s - loss: 0.8998 - categorical_accuracy: 0.6700 - val_loss: 0.9260 - val_categorical_accuracy: 0.6547 - 489ms/epoch - 24ms/step
Epoch 136/1500
20/20 - 0s - loss: 0.9367 - categorical_accuracy: 0.6543 - val_loss: 0.9107 - val_categorical_accuracy: 0.6624 - 485ms/epoch - 24ms/step
Epoch 137/1500
20/20 - 0s - loss: 0.8954 - categorical_accuracy: 0.6710 - val_loss: 0.8979 - val_categorical_accuracy: 0.6690 - 481ms/epoch - 24ms/step
Epoch 138/1500
20/20 - 0s - loss: 0.9029 - categorical_accuracy: 0.6678 - val_loss: 0.9164 - val_categorical_accuracy: 0.6672 - 472ms/epoch - 24ms/step
Epoch 139/1500
20/20 - 0s - loss: 0.9318 - categorical_accuracy: 0.6587 - val_loss: 0.9067 - val_categorical_accuracy: 0.6700 - 484ms/epoch - 24ms/step
Epoch 140/1500
20/20 - 0s - loss: 0.8886 - categorical_accuracy: 0.6741 - val_loss: 0.9121 - val_categorical_accuracy: 0.6653 - 471ms/epoch - 24ms/step
Epoch 141/1500
20/20 - 0s - loss: 0.9020 - categorical_accuracy: 0.6664 - val_loss: 0.9509 - val_categorical_accuracy: 0.6535 - 463ms/epoch - 23ms/step
Epoch 142/1500
20/20 - 0s - loss: 0.9189 - categorical_accuracy: 0.6605 - val_loss: 0.8930 - val_categorical_accuracy: 0.6726 - 458ms/epoch - 23ms/step
Epoch 143/1500
20/20 - 0s - loss: 0.8885 - categorical_accuracy: 0.6717 - val_loss: 0.9045 - val_categorical_accuracy: 0.6675 - 458ms/epoch - 23ms/step
Epoch 144/1500
20/20 - 0s - loss: 0.8923 - categorical_accuracy: 0.6718 - val_loss: 0.8804 - val_categorical_accuracy: 0.6750 - 487ms/epoch - 24ms/step
Epoch 145/1500
20/20 - 0s - loss: 0.8778 - categorical_accuracy: 0.6761 - val_loss: 0.8914 - val_categorical_accuracy: 0.6731 - 474ms/epoch - 24ms/step
Epoch 146/1500
20/20 - 0s - loss: 0.9203 - categorical_accuracy: 0.6598 - val_loss: 0.8898 - val_categorical_accuracy: 0.6740 - 468ms/epoch - 23ms/step
Epoch 147/1500
20/20 - 0s - loss: 0.8664 - categorical_accuracy: 0.6806 - val_loss: 0.8593 - val_categorical_accuracy: 0.6846 - 469ms/epoch - 23ms/step
Epoch 148/1500
20/20 - 1s - loss: 0.8524 - categorical_accuracy: 0.6874 - val_loss: 0.8577 - val_categorical_accuracy: 0.6863 - 506ms/epoch - 25ms/step
Epoch 149/1500
20/20 - 0s - loss: 0.8677 - categorical_accuracy: 0.6808 - val_loss: 0.9310 - val_categorical_accuracy: 0.6594 - 488ms/epoch - 24ms/step
Epoch 150/1500
20/20 - 0s - loss: 0.9081 - categorical_accuracy: 0.6673 - val_loss: 0.9009 - val_categorical_accuracy: 0.6689 - 481ms/epoch - 24ms/step
Epoch 151/1500
20/20 - 0s - loss: 0.8957 - categorical_accuracy: 0.6674 - val_loss: 0.8913 - val_categorical_accuracy: 0.6726 - 486ms/epoch - 24ms/step
Epoch 152/1500
20/20 - 0s - loss: 0.8675 - categorical_accuracy: 0.6789 - val_loss: 0.8648 - val_categorical_accuracy: 0.6804 - 472ms/epoch - 24ms/step
Epoch 153/1500
20/20 - 0s - loss: 0.8473 - categorical_accuracy: 0.6865 - val_loss: 0.8434 - val_categorical_accuracy: 0.6898 - 486ms/epoch - 24ms/step
Epoch 154/1500
20/20 - 0s - loss: 0.8441 - categorical_accuracy: 0.6876 - val_loss: 0.8657 - val_categorical_accuracy: 0.6801 - 482ms/epoch - 24ms/step
Epoch 155/1500
20/20 - 1s - loss: 0.8681 - categorical_accuracy: 0.6781 - val_loss: 0.9052 - val_categorical_accuracy: 0.6687 - 503ms/epoch - 25ms/step
Epoch 156/1500
20/20 - 0s - loss: 0.8716 - categorical_accuracy: 0.6775 - val_loss: 0.8397 - val_categorical_accuracy: 0.6906 - 474ms/epoch - 24ms/step
Epoch 157/1500
20/20 - 0s - loss: 0.8285 - categorical_accuracy: 0.6947 - val_loss: 0.8378 - val_categorical_accuracy: 0.6909 - 490ms/epoch - 25ms/step
Epoch 158/1500
20/20 - 0s - loss: 0.8410 - categorical_accuracy: 0.6914 - val_loss: 0.8610 - val_categorical_accuracy: 0.6800 - 496ms/epoch - 25ms/step
Epoch 159/1500
20/20 - 0s - loss: 0.8589 - categorical_accuracy: 0.6852 - val_loss: 0.8338 - val_categorical_accuracy: 0.6912 - 492ms/epoch - 25ms/step
Epoch 160/1500
20/20 - 0s - loss: 0.8206 - categorical_accuracy: 0.6981 - val_loss: 0.8390 - val_categorical_accuracy: 0.6864 - 477ms/epoch - 24ms/step
Epoch 161/1500
20/20 - 0s - loss: 0.8822 - categorical_accuracy: 0.6710 - val_loss: 0.8561 - val_categorical_accuracy: 0.6801 - 481ms/epoch - 24ms/step
Epoch 162/1500
20/20 - 0s - loss: 0.8345 - categorical_accuracy: 0.6908 - val_loss: 0.8362 - val_categorical_accuracy: 0.6886 - 482ms/epoch - 24ms/step
Epoch 163/1500
20/20 - 0s - loss: 0.8107 - categorical_accuracy: 0.7009 - val_loss: 0.8135 - val_categorical_accuracy: 0.7003 - 483ms/epoch - 24ms/step
Epoch 164/1500
20/20 - 0s - loss: 0.8458 - categorical_accuracy: 0.6864 - val_loss: 0.9027 - val_categorical_accuracy: 0.6612 - 471ms/epoch - 24ms/step
Epoch 165/1500
20/20 - 0s - loss: 0.8331 - categorical_accuracy: 0.6926 - val_loss: 0.8143 - val_categorical_accuracy: 0.7006 - 475ms/epoch - 24ms/step
Epoch 166/1500
20/20 - 0s - loss: 0.8060 - categorical_accuracy: 0.7025 - val_loss: 0.8310 - val_categorical_accuracy: 0.6945 - 467ms/epoch - 23ms/step
Epoch 167/1500
20/20 - 0s - loss: 0.8579 - categorical_accuracy: 0.6803 - val_loss: 0.8392 - val_categorical_accuracy: 0.6911 - 474ms/epoch - 24ms/step
Epoch 168/1500
20/20 - 0s - loss: 0.8057 - categorical_accuracy: 0.7030 - val_loss: 0.8022 - val_categorical_accuracy: 0.7054 - 467ms/epoch - 23ms/step
Epoch 169/1500
20/20 - 0s - loss: 0.8027 - categorical_accuracy: 0.7044 - val_loss: 0.8480 - val_categorical_accuracy: 0.6872 - 467ms/epoch - 23ms/step
Epoch 170/1500
20/20 - 0s - loss: 0.8341 - categorical_accuracy: 0.6943 - val_loss: 0.8281 - val_categorical_accuracy: 0.6940 - 485ms/epoch - 24ms/step
Epoch 171/1500
20/20 - 0s - loss: 0.8509 - categorical_accuracy: 0.6851 - val_loss: 0.8377 - val_categorical_accuracy: 0.6854 - 485ms/epoch - 24ms/step
Epoch 172/1500
20/20 - 0s - loss: 0.8057 - categorical_accuracy: 0.7030 - val_loss: 0.7908 - val_categorical_accuracy: 0.7089 - 478ms/epoch - 24ms/step
Epoch 173/1500
20/20 - 0s - loss: 0.7869 - categorical_accuracy: 0.7104 - val_loss: 0.8070 - val_categorical_accuracy: 0.7017 - 476ms/epoch - 24ms/step
Epoch 174/1500
20/20 - 0s - loss: 0.8132 - categorical_accuracy: 0.6999 - val_loss: 0.8012 - val_categorical_accuracy: 0.7076 - 473ms/epoch - 24ms/step
Epoch 175/1500
20/20 - 0s - loss: 0.7895 - categorical_accuracy: 0.7097 - val_loss: 0.8130 - val_categorical_accuracy: 0.6993 - 471ms/epoch - 24ms/step
Epoch 176/1500
20/20 - 0s - loss: 0.8553 - categorical_accuracy: 0.6851 - val_loss: 0.7857 - val_categorical_accuracy: 0.7111 - 490ms/epoch - 25ms/step
Epoch 177/1500
20/20 - 0s - loss: 0.7763 - categorical_accuracy: 0.7152 - val_loss: 0.8014 - val_categorical_accuracy: 0.7071 - 472ms/epoch - 24ms/step
Epoch 178/1500
20/20 - 0s - loss: 0.8053 - categorical_accuracy: 0.7038 - val_loss: 0.7892 - val_categorical_accuracy: 0.7081 - 472ms/epoch - 24ms/step
Epoch 179/1500
20/20 - 0s - loss: 0.7924 - categorical_accuracy: 0.7090 - val_loss: 0.8335 - val_categorical_accuracy: 0.6909 - 472ms/epoch - 24ms/step
Epoch 180/1500
20/20 - 0s - loss: 0.8064 - categorical_accuracy: 0.7032 - val_loss: 0.7820 - val_categorical_accuracy: 0.7116 - 468ms/epoch - 23ms/step
Epoch 181/1500
20/20 - 0s - loss: 0.7819 - categorical_accuracy: 0.7121 - val_loss: 0.7916 - val_categorical_accuracy: 0.7080 - 470ms/epoch - 24ms/step
Epoch 182/1500
20/20 - 0s - loss: 0.7684 - categorical_accuracy: 0.7180 - val_loss: 0.7781 - val_categorical_accuracy: 0.7148 - 470ms/epoch - 24ms/step
Epoch 183/1500
20/20 - 0s - loss: 0.7807 - categorical_accuracy: 0.7131 - val_loss: 0.8188 - val_categorical_accuracy: 0.6942 - 478ms/epoch - 24ms/step
Epoch 184/1500
20/20 - 0s - loss: 0.8164 - categorical_accuracy: 0.6992 - val_loss: 0.7688 - val_categorical_accuracy: 0.7171 - 472ms/epoch - 24ms/step
Epoch 185/1500
20/20 - 0s - loss: 0.7512 - categorical_accuracy: 0.7250 - val_loss: 0.7567 - val_categorical_accuracy: 0.7232 - 474ms/epoch - 24ms/step
Epoch 186/1500
20/20 - 0s - loss: 0.7541 - categorical_accuracy: 0.7240 - val_loss: 0.7781 - val_categorical_accuracy: 0.7136 - 481ms/epoch - 24ms/step
Epoch 187/1500
20/20 - 0s - loss: 0.8082 - categorical_accuracy: 0.7023 - val_loss: 0.7963 - val_categorical_accuracy: 0.7091 - 493ms/epoch - 25ms/step
Epoch 188/1500
20/20 - 0s - loss: 0.7600 - categorical_accuracy: 0.7213 - val_loss: 0.7961 - val_categorical_accuracy: 0.7095 - 469ms/epoch - 23ms/step
Epoch 189/1500
20/20 - 0s - loss: 0.8299 - categorical_accuracy: 0.6942 - val_loss: 0.7670 - val_categorical_accuracy: 0.7212 - 479ms/epoch - 24ms/step
Epoch 190/1500
20/20 - 0s - loss: 0.7455 - categorical_accuracy: 0.7275 - val_loss: 0.7473 - val_categorical_accuracy: 0.7283 - 482ms/epoch - 24ms/step
Epoch 191/1500
20/20 - 0s - loss: 0.7403 - categorical_accuracy: 0.7287 - val_loss: 0.7631 - val_categorical_accuracy: 0.7185 - 485ms/epoch - 24ms/step
Epoch 192/1500
20/20 - 0s - loss: 0.7869 - categorical_accuracy: 0.7105 - val_loss: 0.8216 - val_categorical_accuracy: 0.6947 - 471ms/epoch - 24ms/step
Epoch 193/1500
20/20 - 0s - loss: 0.7753 - categorical_accuracy: 0.7159 - val_loss: 0.7424 - val_categorical_accuracy: 0.7283 - 491ms/epoch - 25ms/step
Epoch 194/1500
20/20 - 0s - loss: 0.7441 - categorical_accuracy: 0.7275 - val_loss: 0.7604 - val_categorical_accuracy: 0.7192 - 478ms/epoch - 24ms/step
Epoch 195/1500
20/20 - 0s - loss: 0.7461 - categorical_accuracy: 0.7258 - val_loss: 0.7395 - val_categorical_accuracy: 0.7279 - 471ms/epoch - 24ms/step
Epoch 196/1500
20/20 - 0s - loss: 0.7512 - categorical_accuracy: 0.7245 - val_loss: 0.7846 - val_categorical_accuracy: 0.7093 - 481ms/epoch - 24ms/step
Epoch 197/1500
20/20 - 0s - loss: 0.7460 - categorical_accuracy: 0.7262 - val_loss: 0.7590 - val_categorical_accuracy: 0.7189 - 469ms/epoch - 23ms/step
Epoch 198/1500
20/20 - 0s - loss: 0.8446 - categorical_accuracy: 0.6944 - val_loss: 0.7476 - val_categorical_accuracy: 0.7254 - 486ms/epoch - 24ms/step
Epoch 199/1500
20/20 - 0s - loss: 0.7241 - categorical_accuracy: 0.7352 - val_loss: 0.7284 - val_categorical_accuracy: 0.7338 - 477ms/epoch - 24ms/step
Epoch 200/1500
20/20 - 0s - loss: 0.7183 - categorical_accuracy: 0.7365 - val_loss: 0.7267 - val_categorical_accuracy: 0.7330 - 468ms/epoch - 23ms/step
Epoch 201/1500
20/20 - 0s - loss: 0.7681 - categorical_accuracy: 0.7155 - val_loss: 0.8129 - val_categorical_accuracy: 0.6969 - 474ms/epoch - 24ms/step
Epoch 202/1500
20/20 - 0s - loss: 0.7428 - categorical_accuracy: 0.7271 - val_loss: 0.7207 - val_categorical_accuracy: 0.7358 - 469ms/epoch - 23ms/step
Epoch 203/1500
20/20 - 0s - loss: 0.7109 - categorical_accuracy: 0.7387 - val_loss: 0.7198 - val_categorical_accuracy: 0.7378 - 478ms/epoch - 24ms/step
Epoch 204/1500
20/20 - 0s - loss: 0.7087 - categorical_accuracy: 0.7399 - val_loss: 0.7211 - val_categorical_accuracy: 0.7353 - 474ms/epoch - 24ms/step
Epoch 205/1500
20/20 - 0s - loss: 0.8072 - categorical_accuracy: 0.7063 - val_loss: 0.8518 - val_categorical_accuracy: 0.6842 - 477ms/epoch - 24ms/step
Epoch 206/1500
20/20 - 0s - loss: 0.7341 - categorical_accuracy: 0.7308 - val_loss: 0.7138 - val_categorical_accuracy: 0.7393 - 461ms/epoch - 23ms/step
Epoch 207/1500
20/20 - 0s - loss: 0.7026 - categorical_accuracy: 0.7422 - val_loss: 0.7112 - val_categorical_accuracy: 0.7397 - 474ms/epoch - 24ms/step
Epoch 208/1500
20/20 - 0s - loss: 0.7026 - categorical_accuracy: 0.7424 - val_loss: 0.7256 - val_categorical_accuracy: 0.7311 - 474ms/epoch - 24ms/step
Epoch 209/1500
20/20 - 0s - loss: 0.7996 - categorical_accuracy: 0.7047 - val_loss: 0.7422 - val_categorical_accuracy: 0.7279 - 479ms/epoch - 24ms/step
Epoch 210/1500
20/20 - 0s - loss: 0.7085 - categorical_accuracy: 0.7404 - val_loss: 0.7058 - val_categorical_accuracy: 0.7416 - 482ms/epoch - 24ms/step
Epoch 211/1500
20/20 - 0s - loss: 0.6944 - categorical_accuracy: 0.7451 - val_loss: 0.7032 - val_categorical_accuracy: 0.7428 - 492ms/epoch - 25ms/step
Epoch 212/1500
20/20 - 0s - loss: 0.7005 - categorical_accuracy: 0.7430 - val_loss: 0.7486 - val_categorical_accuracy: 0.7281 - 479ms/epoch - 24ms/step
Epoch 213/1500
20/20 - 0s - loss: 0.7914 - categorical_accuracy: 0.7096 - val_loss: 0.7027 - val_categorical_accuracy: 0.7435 - 484ms/epoch - 24ms/step
Epoch 214/1500
20/20 - 0s - loss: 0.7006 - categorical_accuracy: 0.7421 - val_loss: 0.7172 - val_categorical_accuracy: 0.7359 - 484ms/epoch - 24ms/step
Epoch 215/1500
20/20 - 0s - loss: 0.6999 - categorical_accuracy: 0.7427 - val_loss: 0.7031 - val_categorical_accuracy: 0.7411 - 469ms/epoch - 23ms/step
Epoch 216/1500
20/20 - 0s - loss: 0.7226 - categorical_accuracy: 0.7336 - val_loss: 0.7365 - val_categorical_accuracy: 0.7282 - 471ms/epoch - 24ms/step
Epoch 217/1500
20/20 - 0s - loss: 0.7094 - categorical_accuracy: 0.7397 - val_loss: 0.6940 - val_categorical_accuracy: 0.7442 - 472ms/epoch - 24ms/step
Epoch 218/1500
20/20 - 0s - loss: 0.6838 - categorical_accuracy: 0.7487 - val_loss: 0.6985 - val_categorical_accuracy: 0.7445 - 480ms/epoch - 24ms/step
Epoch 219/1500
20/20 - 0s - loss: 0.6852 - categorical_accuracy: 0.7486 - val_loss: 0.7004 - val_categorical_accuracy: 0.7450 - 474ms/epoch - 24ms/step
Epoch 220/1500
20/20 - 0s - loss: 0.7464 - categorical_accuracy: 0.7237 - val_loss: 0.7573 - val_categorical_accuracy: 0.7250 - 474ms/epoch - 24ms/step
Epoch 221/1500
20/20 - 0s - loss: 0.7561 - categorical_accuracy: 0.7233 - val_loss: 0.8721 - val_categorical_accuracy: 0.6920 - 470ms/epoch - 24ms/step
Epoch 222/1500
20/20 - 0s - loss: 0.7227 - categorical_accuracy: 0.7350 - val_loss: 0.6858 - val_categorical_accuracy: 0.7505 - 488ms/epoch - 24ms/step
Epoch 223/1500
20/20 - 0s - loss: 0.6738 - categorical_accuracy: 0.7528 - val_loss: 0.6810 - val_categorical_accuracy: 0.7499 - 473ms/epoch - 24ms/step
Epoch 224/1500
20/20 - 0s - loss: 0.6722 - categorical_accuracy: 0.7530 - val_loss: 0.6797 - val_categorical_accuracy: 0.7505 - 462ms/epoch - 23ms/step
Epoch 225/1500
20/20 - 0s - loss: 0.6726 - categorical_accuracy: 0.7532 - val_loss: 0.6983 - val_categorical_accuracy: 0.7416 - 476ms/epoch - 24ms/step
Epoch 226/1500
20/20 - 0s - loss: 0.8039 - categorical_accuracy: 0.7107 - val_loss: 0.6903 - val_categorical_accuracy: 0.7453 - 476ms/epoch - 24ms/step
Epoch 227/1500
20/20 - 0s - loss: 0.6716 - categorical_accuracy: 0.7536 - val_loss: 0.6801 - val_categorical_accuracy: 0.7513 - 482ms/epoch - 24ms/step
Epoch 228/1500
20/20 - 0s - loss: 0.6671 - categorical_accuracy: 0.7550 - val_loss: 0.6765 - val_categorical_accuracy: 0.7527 - 499ms/epoch - 25ms/step
Epoch 229/1500
20/20 - 1s - loss: 0.7031 - categorical_accuracy: 0.7399 - val_loss: 0.7724 - val_categorical_accuracy: 0.7120 - 516ms/epoch - 26ms/step
Epoch 230/1500
20/20 - 1s - loss: 0.7263 - categorical_accuracy: 0.7320 - val_loss: 0.6725 - val_categorical_accuracy: 0.7526 - 506ms/epoch - 25ms/step
Epoch 231/1500
20/20 - 0s - loss: 0.6618 - categorical_accuracy: 0.7561 - val_loss: 0.6719 - val_categorical_accuracy: 0.7516 - 495ms/epoch - 25ms/step
Epoch 232/1500
20/20 - 1s - loss: 0.6839 - categorical_accuracy: 0.7477 - val_loss: 0.7677 - val_categorical_accuracy: 0.7113 - 500ms/epoch - 25ms/step
Epoch 233/1500
20/20 - 0s - loss: 0.7173 - categorical_accuracy: 0.7343 - val_loss: 0.6680 - val_categorical_accuracy: 0.7535 - 485ms/epoch - 24ms/step
Epoch 234/1500
20/20 - 0s - loss: 0.6630 - categorical_accuracy: 0.7556 - val_loss: 0.6757 - val_categorical_accuracy: 0.7505 - 477ms/epoch - 24ms/step
Epoch 235/1500
20/20 - 0s - loss: 0.6716 - categorical_accuracy: 0.7523 - val_loss: 0.6730 - val_categorical_accuracy: 0.7540 - 488ms/epoch - 24ms/step
Epoch 236/1500
20/20 - 0s - loss: 0.6866 - categorical_accuracy: 0.7479 - val_loss: 0.7774 - val_categorical_accuracy: 0.7139 - 474ms/epoch - 24ms/step
Epoch 237/1500
20/20 - 0s - loss: 0.7220 - categorical_accuracy: 0.7343 - val_loss: 0.6667 - val_categorical_accuracy: 0.7531 - 474ms/epoch - 24ms/step
Epoch 238/1500
20/20 - 0s - loss: 0.6497 - categorical_accuracy: 0.7609 - val_loss: 0.6575 - val_categorical_accuracy: 0.7590 - 466ms/epoch - 23ms/step
Epoch 239/1500
20/20 - 0s - loss: 0.6504 - categorical_accuracy: 0.7611 - val_loss: 0.6670 - val_categorical_accuracy: 0.7536 - 474ms/epoch - 24ms/step
Epoch 240/1500
20/20 - 0s - loss: 0.7101 - categorical_accuracy: 0.7371 - val_loss: 1.2546 - val_categorical_accuracy: 0.6224 - 479ms/epoch - 24ms/step
Epoch 241/1500
20/20 - 0s - loss: 1.0244 - categorical_accuracy: 0.6729 - val_loss: 0.6713 - val_categorical_accuracy: 0.7547 - 473ms/epoch - 24ms/step
Epoch 242/1500
20/20 - 0s - loss: 0.6558 - categorical_accuracy: 0.7604 - val_loss: 0.6624 - val_categorical_accuracy: 0.7575 - 488ms/epoch - 24ms/step
Epoch 243/1500
20/20 - 0s - loss: 0.6480 - categorical_accuracy: 0.7624 - val_loss: 0.6572 - val_categorical_accuracy: 0.7578 - 473ms/epoch - 24ms/step
Epoch 244/1500
20/20 - 0s - loss: 0.6454 - categorical_accuracy: 0.7637 - val_loss: 0.6597 - val_categorical_accuracy: 0.7558 - 485ms/epoch - 24ms/step
Epoch 245/1500
20/20 - 0s - loss: 0.6449 - categorical_accuracy: 0.7637 - val_loss: 0.6571 - val_categorical_accuracy: 0.7576 - 490ms/epoch - 25ms/step
Epoch 246/1500
20/20 - 0s - loss: 0.6477 - categorical_accuracy: 0.7631 - val_loss: 0.6714 - val_categorical_accuracy: 0.7520 - 487ms/epoch - 24ms/step
Epoch 247/1500
20/20 - 0s - loss: 0.6996 - categorical_accuracy: 0.7436 - val_loss: 0.7621 - val_categorical_accuracy: 0.7211 - 494ms/epoch - 25ms/step
Epoch 248/1500
20/20 - 1s - loss: 0.6688 - categorical_accuracy: 0.7549 - val_loss: 0.6502 - val_categorical_accuracy: 0.7601 - 515ms/epoch - 26ms/step
Epoch 249/1500
20/20 - 0s - loss: 0.6375 - categorical_accuracy: 0.7656 - val_loss: 0.6451 - val_categorical_accuracy: 0.7613 - 493ms/epoch - 25ms/step
Epoch 250/1500
20/20 - 0s - loss: 0.6546 - categorical_accuracy: 0.7559 - val_loss: 0.6673 - val_categorical_accuracy: 0.7501 - 498ms/epoch - 25ms/step
Epoch 251/1500
20/20 - 0s - loss: 0.6440 - categorical_accuracy: 0.7616 - val_loss: 0.6445 - val_categorical_accuracy: 0.7630 - 481ms/epoch - 24ms/step
Epoch 252/1500
20/20 - 0s - loss: 0.6385 - categorical_accuracy: 0.7639 - val_loss: 0.6548 - val_categorical_accuracy: 0.7562 - 471ms/epoch - 24ms/step
Epoch 253/1500
20/20 - 0s - loss: 0.6511 - categorical_accuracy: 0.7582 - val_loss: 0.6625 - val_categorical_accuracy: 0.7580 - 488ms/epoch - 24ms/step
Epoch 254/1500
20/20 - 0s - loss: 0.7529 - categorical_accuracy: 0.7270 - val_loss: 0.9086 - val_categorical_accuracy: 0.6660 - 456ms/epoch - 23ms/step
Epoch 255/1500
20/20 - 0s - loss: 0.6771 - categorical_accuracy: 0.7520 - val_loss: 0.6370 - val_categorical_accuracy: 0.7661 - 463ms/epoch - 23ms/step
Epoch 256/1500
20/20 - 0s - loss: 0.6247 - categorical_accuracy: 0.7703 - val_loss: 0.6350 - val_categorical_accuracy: 0.7684 - 457ms/epoch - 23ms/step
Epoch 257/1500
20/20 - 0s - loss: 0.6271 - categorical_accuracy: 0.7692 - val_loss: 0.6539 - val_categorical_accuracy: 0.7562 - 457ms/epoch - 23ms/step
Epoch 258/1500
20/20 - 0s - loss: 0.6490 - categorical_accuracy: 0.7575 - val_loss: 0.6635 - val_categorical_accuracy: 0.7511 - 472ms/epoch - 24ms/step
Epoch 259/1500
20/20 - 0s - loss: 0.6371 - categorical_accuracy: 0.7634 - val_loss: 0.6458 - val_categorical_accuracy: 0.7591 - 456ms/epoch - 23ms/step
Epoch 260/1500
20/20 - 0s - loss: 0.6471 - categorical_accuracy: 0.7595 - val_loss: 0.6510 - val_categorical_accuracy: 0.7561 - 476ms/epoch - 24ms/step
Epoch 261/1500
20/20 - 0s - loss: 0.6424 - categorical_accuracy: 0.7600 - val_loss: 0.6431 - val_categorical_accuracy: 0.7624 - 489ms/epoch - 24ms/step
Epoch 262/1500
20/20 - 0s - loss: 0.6278 - categorical_accuracy: 0.7691 - val_loss: 0.6328 - val_categorical_accuracy: 0.7674 - 470ms/epoch - 24ms/step
Epoch 263/1500
20/20 - 0s - loss: 0.6346 - categorical_accuracy: 0.7665 - val_loss: 0.6507 - val_categorical_accuracy: 0.7620 - 497ms/epoch - 25ms/step
Epoch 264/1500
20/20 - 0s - loss: 0.6265 - categorical_accuracy: 0.7708 - val_loss: 0.6253 - val_categorical_accuracy: 0.7734 - 481ms/epoch - 24ms/step
Epoch 265/1500
20/20 - 0s - loss: 0.7862 - categorical_accuracy: 0.7203 - val_loss: 0.8226 - val_categorical_accuracy: 0.7064 - 474ms/epoch - 24ms/step
Epoch 266/1500
20/20 - 0s - loss: 0.6311 - categorical_accuracy: 0.7698 - val_loss: 0.6222 - val_categorical_accuracy: 0.7738 - 474ms/epoch - 24ms/step
Epoch 267/1500
20/20 - 0s - loss: 0.6100 - categorical_accuracy: 0.7770 - val_loss: 0.6245 - val_categorical_accuracy: 0.7708 - 487ms/epoch - 24ms/step
Epoch 268/1500
20/20 - 0s - loss: 0.6164 - categorical_accuracy: 0.7731 - val_loss: 0.6339 - val_categorical_accuracy: 0.7634 - 494ms/epoch - 25ms/step
Epoch 269/1500
20/20 - 0s - loss: 0.6389 - categorical_accuracy: 0.7606 - val_loss: 0.6268 - val_categorical_accuracy: 0.7672 - 489ms/epoch - 24ms/step
Epoch 270/1500
20/20 - 0s - loss: 0.6244 - categorical_accuracy: 0.7678 - val_loss: 0.6338 - val_categorical_accuracy: 0.7626 - 484ms/epoch - 24ms/step
Epoch 271/1500
20/20 - 0s - loss: 0.6223 - categorical_accuracy: 0.7688 - val_loss: 0.6244 - val_categorical_accuracy: 0.7673 - 488ms/epoch - 24ms/step
Epoch 272/1500
20/20 - 0s - loss: 0.6216 - categorical_accuracy: 0.7693 - val_loss: 0.6494 - val_categorical_accuracy: 0.7553 - 481ms/epoch - 24ms/step
Epoch 273/1500
20/20 - 0s - loss: 0.6180 - categorical_accuracy: 0.7713 - val_loss: 0.6193 - val_categorical_accuracy: 0.7699 - 483ms/epoch - 24ms/step
Epoch 274/1500
20/20 - 0s - loss: 0.6206 - categorical_accuracy: 0.7690 - val_loss: 0.6335 - val_categorical_accuracy: 0.7623 - 476ms/epoch - 24ms/step
Epoch 275/1500
20/20 - 1s - loss: 0.6185 - categorical_accuracy: 0.7702 - val_loss: 0.6112 - val_categorical_accuracy: 0.7743 - 506ms/epoch - 25ms/step
Epoch 276/1500
20/20 - 0s - loss: 0.6446 - categorical_accuracy: 0.7628 - val_loss: 0.8303 - val_categorical_accuracy: 0.7070 - 474ms/epoch - 24ms/step
Epoch 277/1500
20/20 - 0s - loss: 0.7550 - categorical_accuracy: 0.7290 - val_loss: 0.6115 - val_categorical_accuracy: 0.7773 - 471ms/epoch - 24ms/step
Epoch 278/1500
20/20 - 0s - loss: 0.5959 - categorical_accuracy: 0.7824 - val_loss: 0.6044 - val_categorical_accuracy: 0.7788 - 480ms/epoch - 24ms/step
Epoch 279/1500
20/20 - 1s - loss: 0.5952 - categorical_accuracy: 0.7825 - val_loss: 0.6077 - val_categorical_accuracy: 0.7740 - 506ms/epoch - 25ms/step
Epoch 280/1500
20/20 - 1s - loss: 0.6122 - categorical_accuracy: 0.7720 - val_loss: 0.6207 - val_categorical_accuracy: 0.7684 - 500ms/epoch - 25ms/step
Epoch 281/1500
20/20 - 1s - loss: 0.6053 - categorical_accuracy: 0.7765 - val_loss: 0.6157 - val_categorical_accuracy: 0.7737 - 504ms/epoch - 25ms/step
Epoch 282/1500
20/20 - 1s - loss: 0.6096 - categorical_accuracy: 0.7748 - val_loss: 0.6278 - val_categorical_accuracy: 0.7645 - 502ms/epoch - 25ms/step
Epoch 283/1500
20/20 - 1s - loss: 0.6023 - categorical_accuracy: 0.7777 - val_loss: 0.6035 - val_categorical_accuracy: 0.7768 - 502ms/epoch - 25ms/step
Epoch 284/1500
20/20 - 1s - loss: 0.5944 - categorical_accuracy: 0.7818 - val_loss: 0.6668 - val_categorical_accuracy: 0.7480 - 500ms/epoch - 25ms/step
Epoch 285/1500
20/20 - 0s - loss: 0.6261 - categorical_accuracy: 0.7676 - val_loss: 0.5953 - val_categorical_accuracy: 0.7819 - 484ms/epoch - 24ms/step
Epoch 286/1500
20/20 - 0s - loss: 0.5879 - categorical_accuracy: 0.7854 - val_loss: 0.6248 - val_categorical_accuracy: 0.7657 - 486ms/epoch - 24ms/step
Epoch 287/1500
20/20 - 0s - loss: 0.6302 - categorical_accuracy: 0.7648 - val_loss: 0.6186 - val_categorical_accuracy: 0.7686 - 490ms/epoch - 25ms/step
Epoch 288/1500
20/20 - 0s - loss: 0.6006 - categorical_accuracy: 0.7787 - val_loss: 0.6210 - val_categorical_accuracy: 0.7696 - 478ms/epoch - 24ms/step
Epoch 289/1500
20/20 - 0s - loss: 0.6129 - categorical_accuracy: 0.7730 - val_loss: 0.6554 - val_categorical_accuracy: 0.7575 - 476ms/epoch - 24ms/step
Epoch 290/1500
20/20 - 0s - loss: 0.7322 - categorical_accuracy: 0.7357 - val_loss: 0.6243 - val_categorical_accuracy: 0.7777 - 498ms/epoch - 25ms/step
Epoch 291/1500
20/20 - 0s - loss: 0.5834 - categorical_accuracy: 0.7876 - val_loss: 0.5952 - val_categorical_accuracy: 0.7848 - 470ms/epoch - 24ms/step
Epoch 292/1500
20/20 - 0s - loss: 0.5770 - categorical_accuracy: 0.7900 - val_loss: 0.5874 - val_categorical_accuracy: 0.7860 - 482ms/epoch - 24ms/step
Epoch 293/1500
20/20 - 0s - loss: 0.5849 - categorical_accuracy: 0.7857 - val_loss: 0.6548 - val_categorical_accuracy: 0.7574 - 486ms/epoch - 24ms/step
Epoch 294/1500
20/20 - 0s - loss: 0.6243 - categorical_accuracy: 0.7665 - val_loss: 0.6008 - val_categorical_accuracy: 0.7815 - 489ms/epoch - 24ms/step
Epoch 295/1500
20/20 - 0s - loss: 0.5796 - categorical_accuracy: 0.7887 - val_loss: 0.6158 - val_categorical_accuracy: 0.7706 - 481ms/epoch - 24ms/step
Epoch 296/1500
20/20 - 0s - loss: 0.6019 - categorical_accuracy: 0.7769 - val_loss: 0.6166 - val_categorical_accuracy: 0.7703 - 498ms/epoch - 25ms/step
Epoch 297/1500
20/20 - 0s - loss: 0.5978 - categorical_accuracy: 0.7780 - val_loss: 0.5984 - val_categorical_accuracy: 0.7830 - 488ms/epoch - 24ms/step
Epoch 298/1500
20/20 - 0s - loss: 0.5927 - categorical_accuracy: 0.7810 - val_loss: 0.5991 - val_categorical_accuracy: 0.7811 - 488ms/epoch - 24ms/step
Epoch 299/1500
20/20 - 0s - loss: 0.6009 - categorical_accuracy: 0.7796 - val_loss: 0.6211 - val_categorical_accuracy: 0.7784 - 479ms/epoch - 24ms/step
Epoch 300/1500
20/20 - 0s - loss: 0.6166 - categorical_accuracy: 0.7767 - val_loss: 0.5918 - val_categorical_accuracy: 0.7887 - 488ms/epoch - 24ms/step
Epoch 301/1500
20/20 - 0s - loss: 0.5684 - categorical_accuracy: 0.7921 - val_loss: 0.5882 - val_categorical_accuracy: 0.7851 - 482ms/epoch - 24ms/step
Epoch 302/1500
20/20 - 0s - loss: 0.5985 - categorical_accuracy: 0.7773 - val_loss: 0.6302 - val_categorical_accuracy: 0.7636 - 488ms/epoch - 24ms/step
Epoch 303/1500
20/20 - 0s - loss: 0.5909 - categorical_accuracy: 0.7810 - val_loss: 0.6041 - val_categorical_accuracy: 0.7780 - 474ms/epoch - 24ms/step
Epoch 304/1500
20/20 - 0s - loss: 0.5825 - categorical_accuracy: 0.7856 - val_loss: 0.5973 - val_categorical_accuracy: 0.7802 - 466ms/epoch - 23ms/step
Epoch 305/1500
20/20 - 0s - loss: 0.5847 - categorical_accuracy: 0.7842 - val_loss: 0.5878 - val_categorical_accuracy: 0.7858 - 467ms/epoch - 23ms/step
Epoch 306/1500
20/20 - 0s - loss: 0.5729 - categorical_accuracy: 0.7916 - val_loss: 0.6737 - val_categorical_accuracy: 0.7590 - 484ms/epoch - 24ms/step
Epoch 307/1500
20/20 - 0s - loss: 0.8065 - categorical_accuracy: 0.7323 - val_loss: 0.5784 - val_categorical_accuracy: 0.7899 - 486ms/epoch - 24ms/step
Epoch 308/1500
20/20 - 0s - loss: 0.5631 - categorical_accuracy: 0.7953 - val_loss: 0.5734 - val_categorical_accuracy: 0.7903 - 472ms/epoch - 24ms/step
Epoch 309/1500
20/20 - 0s - loss: 0.5580 - categorical_accuracy: 0.7970 - val_loss: 0.5683 - val_categorical_accuracy: 0.7926 - 466ms/epoch - 23ms/step
Epoch 310/1500
20/20 - 0s - loss: 0.5655 - categorical_accuracy: 0.7932 - val_loss: 0.6171 - val_categorical_accuracy: 0.7711 - 486ms/epoch - 24ms/step
Epoch 311/1500
20/20 - 0s - loss: 0.6104 - categorical_accuracy: 0.7708 - val_loss: 0.6181 - val_categorical_accuracy: 0.7718 - 470ms/epoch - 24ms/step
Epoch 312/1500
20/20 - 0s - loss: 0.5726 - categorical_accuracy: 0.7903 - val_loss: 0.5656 - val_categorical_accuracy: 0.7944 - 473ms/epoch - 24ms/step
Epoch 313/1500
20/20 - 0s - loss: 0.5640 - categorical_accuracy: 0.7935 - val_loss: 0.6013 - val_categorical_accuracy: 0.7772 - 493ms/epoch - 25ms/step
Epoch 314/1500
20/20 - 0s - loss: 0.5879 - categorical_accuracy: 0.7811 - val_loss: 0.5918 - val_categorical_accuracy: 0.7823 - 478ms/epoch - 24ms/step
Epoch 315/1500
20/20 - 0s - loss: 0.5717 - categorical_accuracy: 0.7920 - val_loss: 0.6369 - val_categorical_accuracy: 0.7692 - 489ms/epoch - 24ms/step
Epoch 316/1500
20/20 - 0s - loss: 0.6606 - categorical_accuracy: 0.7655 - val_loss: 0.5678 - val_categorical_accuracy: 0.7906 - 489ms/epoch - 24ms/step
Epoch 317/1500
20/20 - 0s - loss: 0.5633 - categorical_accuracy: 0.7931 - val_loss: 0.5695 - val_categorical_accuracy: 0.7886 - 490ms/epoch - 25ms/step
Epoch 318/1500
20/20 - 1s - loss: 0.5629 - categorical_accuracy: 0.7942 - val_loss: 0.5812 - val_categorical_accuracy: 0.7836 - 502ms/epoch - 25ms/step
Epoch 319/1500
20/20 - 0s - loss: 0.5760 - categorical_accuracy: 0.7872 - val_loss: 0.6011 - val_categorical_accuracy: 0.7736 - 492ms/epoch - 25ms/step
Epoch 320/1500
20/20 - 0s - loss: 0.5674 - categorical_accuracy: 0.7913 - val_loss: 0.5645 - val_categorical_accuracy: 0.7934 - 486ms/epoch - 24ms/step
Epoch 321/1500
20/20 - 0s - loss: 0.5538 - categorical_accuracy: 0.7973 - val_loss: 0.5841 - val_categorical_accuracy: 0.7805 - 493ms/epoch - 25ms/step
Epoch 322/1500
20/20 - 1s - loss: 0.5829 - categorical_accuracy: 0.7838 - val_loss: 0.6047 - val_categorical_accuracy: 0.7714 - 502ms/epoch - 25ms/step
Epoch 323/1500
20/20 - 1s - loss: 0.5631 - categorical_accuracy: 0.7932 - val_loss: 0.5733 - val_categorical_accuracy: 0.7859 - 505ms/epoch - 25ms/step
Epoch 324/1500
20/20 - 1s - loss: 0.5571 - categorical_accuracy: 0.7977 - val_loss: 0.5756 - val_categorical_accuracy: 0.7883 - 510ms/epoch - 26ms/step
Epoch 325/1500
20/20 - 0s - loss: 0.5745 - categorical_accuracy: 0.7910 - val_loss: 0.6286 - val_categorical_accuracy: 0.7673 - 496ms/epoch - 25ms/step
Epoch 326/1500
20/20 - 1s - loss: 0.6997 - categorical_accuracy: 0.7494 - val_loss: 0.6373 - val_categorical_accuracy: 0.7689 - 507ms/epoch - 25ms/step
Epoch 327/1500
20/20 - 0s - loss: 0.5509 - categorical_accuracy: 0.7994 - val_loss: 0.5531 - val_categorical_accuracy: 0.8016 - 490ms/epoch - 25ms/step
Epoch 328/1500
20/20 - 1s - loss: 0.5394 - categorical_accuracy: 0.8044 - val_loss: 0.5535 - val_categorical_accuracy: 0.8008 - 501ms/epoch - 25ms/step
Epoch 329/1500
20/20 - 0s - loss: 0.5590 - categorical_accuracy: 0.7947 - val_loss: 0.6056 - val_categorical_accuracy: 0.7758 - 489ms/epoch - 24ms/step
Epoch 330/1500
20/20 - 0s - loss: 0.5688 - categorical_accuracy: 0.7898 - val_loss: 0.5777 - val_categorical_accuracy: 0.7877 - 494ms/epoch - 25ms/step
Epoch 331/1500
20/20 - 0s - loss: 0.5575 - categorical_accuracy: 0.7948 - val_loss: 0.5678 - val_categorical_accuracy: 0.7965 - 490ms/epoch - 25ms/step
Epoch 332/1500
20/20 - 0s - loss: 0.5461 - categorical_accuracy: 0.8021 - val_loss: 0.5633 - val_categorical_accuracy: 0.7979 - 496ms/epoch - 25ms/step
Epoch 333/1500
20/20 - 0s - loss: 0.5593 - categorical_accuracy: 0.7950 - val_loss: 0.5666 - val_categorical_accuracy: 0.7948 - 489ms/epoch - 24ms/step
Epoch 334/1500
20/20 - 1s - loss: 0.5625 - categorical_accuracy: 0.7929 - val_loss: 0.5877 - val_categorical_accuracy: 0.7847 - 507ms/epoch - 25ms/step
Epoch 335/1500
20/20 - 1s - loss: 0.5453 - categorical_accuracy: 0.8003 - val_loss: 0.5646 - val_categorical_accuracy: 0.7926 - 502ms/epoch - 25ms/step
Epoch 336/1500
20/20 - 0s - loss: 0.5534 - categorical_accuracy: 0.7972 - val_loss: 0.5814 - val_categorical_accuracy: 0.7903 - 490ms/epoch - 25ms/step
Epoch 337/1500
20/20 - 0s - loss: 0.5563 - categorical_accuracy: 0.7965 - val_loss: 0.5744 - val_categorical_accuracy: 0.7928 - 499ms/epoch - 25ms/step
Epoch 338/1500
20/20 - 0s - loss: 0.5606 - categorical_accuracy: 0.7946 - val_loss: 0.5862 - val_categorical_accuracy: 0.7869 - 489ms/epoch - 24ms/step
Epoch 339/1500
20/20 - 1s - loss: 0.5452 - categorical_accuracy: 0.8006 - val_loss: 0.5409 - val_categorical_accuracy: 0.8030 - 504ms/epoch - 25ms/step
Epoch 340/1500
20/20 - 1s - loss: 0.5753 - categorical_accuracy: 0.7928 - val_loss: 1.0290 - val_categorical_accuracy: 0.6697 - 500ms/epoch - 25ms/step
Epoch 341/1500
20/20 - 1s - loss: 1.1113 - categorical_accuracy: 0.6988 - val_loss: 0.5663 - val_categorical_accuracy: 0.7950 - 503ms/epoch - 25ms/step
Epoch 342/1500
20/20 - 1s - loss: 0.5458 - categorical_accuracy: 0.8042 - val_loss: 0.5534 - val_categorical_accuracy: 0.8026 - 517ms/epoch - 26ms/step
Epoch 343/1500
20/20 - 1s - loss: 0.5352 - categorical_accuracy: 0.8079 - val_loss: 0.5458 - val_categorical_accuracy: 0.8032 - 509ms/epoch - 25ms/step
Epoch 344/1500
20/20 - 0s - loss: 0.5303 - categorical_accuracy: 0.8095 - val_loss: 0.5416 - val_categorical_accuracy: 0.8062 - 482ms/epoch - 24ms/step
Epoch 345/1500
20/20 - 1s - loss: 0.5272 - categorical_accuracy: 0.8104 - val_loss: 0.5444 - val_categorical_accuracy: 0.8052 - 504ms/epoch - 25ms/step
Epoch 346/1500
20/20 - 0s - loss: 0.5322 - categorical_accuracy: 0.8075 - val_loss: 0.5565 - val_categorical_accuracy: 0.7983 - 479ms/epoch - 24ms/step
Epoch 347/1500
20/20 - 0s - loss: 0.5365 - categorical_accuracy: 0.8047 - val_loss: 0.5820 - val_categorical_accuracy: 0.7869 - 474ms/epoch - 24ms/step
Epoch 348/1500
20/20 - 0s - loss: 0.5594 - categorical_accuracy: 0.7935 - val_loss: 0.5506 - val_categorical_accuracy: 0.8004 - 470ms/epoch - 24ms/step
Epoch 349/1500
20/20 - 0s - loss: 0.5486 - categorical_accuracy: 0.7992 - val_loss: 0.5681 - val_categorical_accuracy: 0.7927 - 472ms/epoch - 24ms/step
Epoch 350/1500
20/20 - 0s - loss: 0.5431 - categorical_accuracy: 0.8018 - val_loss: 0.5414 - val_categorical_accuracy: 0.8047 - 472ms/epoch - 24ms/step
Epoch 351/1500
20/20 - 0s - loss: 0.5246 - categorical_accuracy: 0.8104 - val_loss: 0.5530 - val_categorical_accuracy: 0.8003 - 472ms/epoch - 24ms/step
Epoch 352/1500
20/20 - 0s - loss: 0.5456 - categorical_accuracy: 0.8002 - val_loss: 0.5583 - val_categorical_accuracy: 0.7987 - 484ms/epoch - 24ms/step
Epoch 353/1500
20/20 - 0s - loss: 0.5355 - categorical_accuracy: 0.8054 - val_loss: 0.5282 - val_categorical_accuracy: 0.8086 - 482ms/epoch - 24ms/step
Epoch 354/1500
20/20 - 0s - loss: 0.5167 - categorical_accuracy: 0.8126 - val_loss: 0.5420 - val_categorical_accuracy: 0.8031 - 480ms/epoch - 24ms/step
Epoch 355/1500
20/20 - 0s - loss: 0.5643 - categorical_accuracy: 0.7938 - val_loss: 0.7957 - val_categorical_accuracy: 0.7266 - 470ms/epoch - 24ms/step
Epoch 356/1500
20/20 - 0s - loss: 0.7765 - categorical_accuracy: 0.7501 - val_loss: 0.5344 - val_categorical_accuracy: 0.8055 - 487ms/epoch - 24ms/step
Epoch 357/1500
20/20 - 0s - loss: 0.5159 - categorical_accuracy: 0.8149 - val_loss: 0.5267 - val_categorical_accuracy: 0.8109 - 474ms/epoch - 24ms/step
Epoch 358/1500
20/20 - 0s - loss: 0.5118 - categorical_accuracy: 0.8163 - val_loss: 0.5273 - val_categorical_accuracy: 0.8111 - 478ms/epoch - 24ms/step
Epoch 359/1500
20/20 - 0s - loss: 0.5093 - categorical_accuracy: 0.8170 - val_loss: 0.5345 - val_categorical_accuracy: 0.8033 - 468ms/epoch - 23ms/step
Epoch 360/1500
20/20 - 0s - loss: 0.5532 - categorical_accuracy: 0.7964 - val_loss: 0.6076 - val_categorical_accuracy: 0.7715 - 478ms/epoch - 24ms/step
Epoch 361/1500
20/20 - 0s - loss: 0.5526 - categorical_accuracy: 0.7962 - val_loss: 0.5250 - val_categorical_accuracy: 0.8093 - 490ms/epoch - 25ms/step
Epoch 362/1500
20/20 - 0s - loss: 0.5098 - categorical_accuracy: 0.8162 - val_loss: 0.5495 - val_categorical_accuracy: 0.8027 - 474ms/epoch - 24ms/step
Epoch 363/1500
20/20 - 0s - loss: 0.5388 - categorical_accuracy: 0.8029 - val_loss: 0.5487 - val_categorical_accuracy: 0.8034 - 472ms/epoch - 24ms/step
Epoch 364/1500
20/20 - 0s - loss: 0.5221 - categorical_accuracy: 0.8107 - val_loss: 0.5414 - val_categorical_accuracy: 0.8035 - 489ms/epoch - 24ms/step
Epoch 365/1500
20/20 - 0s - loss: 0.5273 - categorical_accuracy: 0.8072 - val_loss: 0.5374 - val_categorical_accuracy: 0.8078 - 474ms/epoch - 24ms/step
Epoch 366/1500
20/20 - 0s - loss: 0.5249 - categorical_accuracy: 0.8093 - val_loss: 0.5591 - val_categorical_accuracy: 0.7992 - 468ms/epoch - 23ms/step
Epoch 367/1500
20/20 - 0s - loss: 0.5210 - categorical_accuracy: 0.8107 - val_loss: 0.5489 - val_categorical_accuracy: 0.8023 - 469ms/epoch - 23ms/step
Epoch 368/1500
20/20 - 0s - loss: 0.5297 - categorical_accuracy: 0.8066 - val_loss: 0.5453 - val_categorical_accuracy: 0.8064 - 474ms/epoch - 24ms/step
Epoch 369/1500
20/20 - 0s - loss: 0.5369 - categorical_accuracy: 0.8047 - val_loss: 0.5315 - val_categorical_accuracy: 0.8103 - 488ms/epoch - 24ms/step
Epoch 370/1500
20/20 - 0s - loss: 0.5065 - categorical_accuracy: 0.8180 - val_loss: 0.5150 - val_categorical_accuracy: 0.8177 - 490ms/epoch - 25ms/step
Epoch 371/1500
20/20 - 1s - loss: 0.4998 - categorical_accuracy: 0.8208 - val_loss: 0.5169 - val_categorical_accuracy: 0.8160 - 503ms/epoch - 25ms/step
Epoch 372/1500
20/20 - 1s - loss: 0.5145 - categorical_accuracy: 0.8129 - val_loss: 0.5676 - val_categorical_accuracy: 0.7966 - 503ms/epoch - 25ms/step
Epoch 373/1500
20/20 - 1s - loss: 0.5541 - categorical_accuracy: 0.7955 - val_loss: 0.5310 - val_categorical_accuracy: 0.8098 - 502ms/epoch - 25ms/step
Epoch 374/1500
20/20 - 0s - loss: 0.5089 - categorical_accuracy: 0.8147 - val_loss: 0.5232 - val_categorical_accuracy: 0.8081 - 490ms/epoch - 25ms/step
Epoch 375/1500
20/20 - 0s - loss: 0.5125 - categorical_accuracy: 0.8136 - val_loss: 0.5218 - val_categorical_accuracy: 0.8137 - 488ms/epoch - 24ms/step
Epoch 376/1500
20/20 - 0s - loss: 0.5186 - categorical_accuracy: 0.8124 - val_loss: 0.5604 - val_categorical_accuracy: 0.7967 - 480ms/epoch - 24ms/step
Epoch 377/1500
20/20 - 0s - loss: 0.5336 - categorical_accuracy: 0.8054 - val_loss: 0.5748 - val_categorical_accuracy: 0.8010 - 488ms/epoch - 24ms/step
Epoch 378/1500
20/20 - 0s - loss: 0.8035 - categorical_accuracy: 0.7410 - val_loss: 0.5197 - val_categorical_accuracy: 0.8158 - 488ms/epoch - 24ms/step
Epoch 379/1500
20/20 - 0s - loss: 0.4999 - categorical_accuracy: 0.8217 - val_loss: 0.5135 - val_categorical_accuracy: 0.8143 - 487ms/epoch - 24ms/step
Epoch 380/1500
20/20 - 0s - loss: 0.4950 - categorical_accuracy: 0.8232 - val_loss: 0.5065 - val_categorical_accuracy: 0.8182 - 481ms/epoch - 24ms/step
Epoch 381/1500
20/20 - 0s - loss: 0.4897 - categorical_accuracy: 0.8252 - val_loss: 0.5043 - val_categorical_accuracy: 0.8212 - 482ms/epoch - 24ms/step
Epoch 382/1500
20/20 - 0s - loss: 0.5042 - categorical_accuracy: 0.8180 - val_loss: 0.5439 - val_categorical_accuracy: 0.8013 - 476ms/epoch - 24ms/step
Epoch 383/1500
20/20 - 0s - loss: 0.5159 - categorical_accuracy: 0.8125 - val_loss: 0.5308 - val_categorical_accuracy: 0.8096 - 470ms/epoch - 24ms/step
Epoch 384/1500
20/20 - 0s - loss: 0.5133 - categorical_accuracy: 0.8140 - val_loss: 0.5316 - val_categorical_accuracy: 0.8078 - 484ms/epoch - 24ms/step
Epoch 385/1500
20/20 - 0s - loss: 0.5128 - categorical_accuracy: 0.8126 - val_loss: 0.5092 - val_categorical_accuracy: 0.8205 - 475ms/epoch - 24ms/step
Epoch 386/1500
20/20 - 0s - loss: 0.5010 - categorical_accuracy: 0.8196 - val_loss: 0.5293 - val_categorical_accuracy: 0.8086 - 484ms/epoch - 24ms/step
Epoch 387/1500
20/20 - 0s - loss: 0.5011 - categorical_accuracy: 0.8183 - val_loss: 0.5092 - val_categorical_accuracy: 0.8137 - 484ms/epoch - 24ms/step
Epoch 388/1500
20/20 - 0s - loss: 0.5021 - categorical_accuracy: 0.8182 - val_loss: 0.5470 - val_categorical_accuracy: 0.8036 - 480ms/epoch - 24ms/step
Epoch 389/1500
20/20 - 0s - loss: 0.5156 - categorical_accuracy: 0.8129 - val_loss: 0.5120 - val_categorical_accuracy: 0.8196 - 488ms/epoch - 24ms/step
Epoch 390/1500
20/20 - 0s - loss: 0.4988 - categorical_accuracy: 0.8194 - val_loss: 0.5031 - val_categorical_accuracy: 0.8224 - 483ms/epoch - 24ms/step
Epoch 391/1500
20/20 - 0s - loss: 0.4848 - categorical_accuracy: 0.8266 - val_loss: 0.5064 - val_categorical_accuracy: 0.8206 - 471ms/epoch - 24ms/step
Epoch 392/1500
20/20 - 0s - loss: 0.5223 - categorical_accuracy: 0.8106 - val_loss: 0.5352 - val_categorical_accuracy: 0.8061 - 486ms/epoch - 24ms/step
Epoch 393/1500
20/20 - 0s - loss: 0.5042 - categorical_accuracy: 0.8160 - val_loss: 0.5011 - val_categorical_accuracy: 0.8226 - 481ms/epoch - 24ms/step
Epoch 394/1500
20/20 - 0s - loss: 0.4911 - categorical_accuracy: 0.8235 - val_loss: 0.5118 - val_categorical_accuracy: 0.8142 - 481ms/epoch - 24ms/step
Epoch 395/1500
20/20 - 0s - loss: 0.4937 - categorical_accuracy: 0.8215 - val_loss: 0.5265 - val_categorical_accuracy: 0.8102 - 476ms/epoch - 24ms/step
Epoch 396/1500
20/20 - 0s - loss: 0.5094 - categorical_accuracy: 0.8146 - val_loss: 0.5378 - val_categorical_accuracy: 0.8103 - 494ms/epoch - 25ms/step
Epoch 397/1500
20/20 - 0s - loss: 0.4970 - categorical_accuracy: 0.8209 - val_loss: 0.5038 - val_categorical_accuracy: 0.8234 - 486ms/epoch - 24ms/step
Epoch 398/1500
20/20 - 0s - loss: 0.4947 - categorical_accuracy: 0.8220 - val_loss: 0.5032 - val_categorical_accuracy: 0.8151 - 493ms/epoch - 25ms/step
Epoch 399/1500
20/20 - 0s - loss: 0.5058 - categorical_accuracy: 0.8098 - val_loss: 0.5694 - val_categorical_accuracy: 0.7830 - 480ms/epoch - 24ms/step
Epoch 400/1500
20/20 - 0s - loss: 0.4967 - categorical_accuracy: 0.8152 - val_loss: 0.4904 - val_categorical_accuracy: 0.8246 - 479ms/epoch - 24ms/step
Epoch 401/1500
20/20 - 0s - loss: 0.4939 - categorical_accuracy: 0.8204 - val_loss: 0.5577 - val_categorical_accuracy: 0.7984 - 475ms/epoch - 24ms/step
Epoch 402/1500
20/20 - 0s - loss: 0.5300 - categorical_accuracy: 0.8060 - val_loss: 0.5093 - val_categorical_accuracy: 0.8168 - 471ms/epoch - 24ms/step
Epoch 403/1500
20/20 - 0s - loss: 0.4846 - categorical_accuracy: 0.8256 - val_loss: 0.5060 - val_categorical_accuracy: 0.8213 - 486ms/epoch - 24ms/step
Epoch 404/1500
20/20 - 0s - loss: 0.5043 - categorical_accuracy: 0.8188 - val_loss: 0.5392 - val_categorical_accuracy: 0.8117 - 480ms/epoch - 24ms/step
Epoch 405/1500
20/20 - 0s - loss: 0.7764 - categorical_accuracy: 0.7442 - val_loss: 0.5453 - val_categorical_accuracy: 0.8074 - 486ms/epoch - 24ms/step
Epoch 406/1500
20/20 - 0s - loss: 0.4821 - categorical_accuracy: 0.8287 - val_loss: 0.4897 - val_categorical_accuracy: 0.8252 - 482ms/epoch - 24ms/step
Epoch 407/1500
20/20 - 0s - loss: 0.4728 - categorical_accuracy: 0.8314 - val_loss: 0.4881 - val_categorical_accuracy: 0.8242 - 487ms/epoch - 24ms/step
Epoch 408/1500
20/20 - 0s - loss: 0.4782 - categorical_accuracy: 0.8264 - val_loss: 0.5061 - val_categorical_accuracy: 0.8099 - 473ms/epoch - 24ms/step
Epoch 409/1500
20/20 - 0s - loss: 0.4870 - categorical_accuracy: 0.8184 - val_loss: 0.4913 - val_categorical_accuracy: 0.8206 - 480ms/epoch - 24ms/step
Epoch 410/1500
20/20 - 0s - loss: 0.4955 - categorical_accuracy: 0.8163 - val_loss: 0.5317 - val_categorical_accuracy: 0.8035 - 472ms/epoch - 24ms/step
Epoch 411/1500
20/20 - 0s - loss: 0.5100 - categorical_accuracy: 0.8139 - val_loss: 0.4910 - val_categorical_accuracy: 0.8212 - 465ms/epoch - 23ms/step
Epoch 412/1500
20/20 - 0s - loss: 0.4839 - categorical_accuracy: 0.8219 - val_loss: 0.4898 - val_categorical_accuracy: 0.8191 - 473ms/epoch - 24ms/step
Epoch 413/1500
20/20 - 0s - loss: 0.4888 - categorical_accuracy: 0.8174 - val_loss: 0.5077 - val_categorical_accuracy: 0.8064 - 474ms/epoch - 24ms/step
Epoch 414/1500
20/20 - 0s - loss: 0.4854 - categorical_accuracy: 0.8181 - val_loss: 0.4917 - val_categorical_accuracy: 0.8176 - 473ms/epoch - 24ms/step
Epoch 415/1500
20/20 - 0s - loss: 0.4811 - categorical_accuracy: 0.8215 - val_loss: 0.4897 - val_categorical_accuracy: 0.8248 - 479ms/epoch - 24ms/step
Epoch 416/1500
20/20 - 0s - loss: 0.5147 - categorical_accuracy: 0.8125 - val_loss: 0.5522 - val_categorical_accuracy: 0.8025 - 480ms/epoch - 24ms/step
Epoch 417/1500
20/20 - 0s - loss: 0.4888 - categorical_accuracy: 0.8248 - val_loss: 0.4855 - val_categorical_accuracy: 0.8268 - 491ms/epoch - 25ms/step
Epoch 418/1500
20/20 - 0s - loss: 0.4754 - categorical_accuracy: 0.8271 - val_loss: 0.5191 - val_categorical_accuracy: 0.8041 - 484ms/epoch - 24ms/step
Epoch 419/1500
20/20 - 0s - loss: 0.4810 - categorical_accuracy: 0.8234 - val_loss: 0.4833 - val_categorical_accuracy: 0.8249 - 472ms/epoch - 24ms/step
Epoch 420/1500
20/20 - 0s - loss: 0.4727 - categorical_accuracy: 0.8261 - val_loss: 0.4992 - val_categorical_accuracy: 0.8130 - 472ms/epoch - 24ms/step
Epoch 421/1500
20/20 - 0s - loss: 0.4866 - categorical_accuracy: 0.8176 - val_loss: 0.4852 - val_categorical_accuracy: 0.8204 - 480ms/epoch - 24ms/step
Epoch 422/1500
20/20 - 0s - loss: 0.5083 - categorical_accuracy: 0.8157 - val_loss: 0.5368 - val_categorical_accuracy: 0.7974 - 485ms/epoch - 24ms/step
Epoch 423/1500
20/20 - 0s - loss: 0.4708 - categorical_accuracy: 0.8316 - val_loss: 0.4749 - val_categorical_accuracy: 0.8275 - 484ms/epoch - 24ms/step
Epoch 424/1500
20/20 - 0s - loss: 0.4676 - categorical_accuracy: 0.8323 - val_loss: 0.5224 - val_categorical_accuracy: 0.8027 - 489ms/epoch - 24ms/step
Epoch 425/1500
20/20 - 1s - loss: 0.4926 - categorical_accuracy: 0.8143 - val_loss: 0.4953 - val_categorical_accuracy: 0.8169 - 503ms/epoch - 25ms/step
Epoch 426/1500
20/20 - 1s - loss: 0.4815 - categorical_accuracy: 0.8220 - val_loss: 0.5398 - val_categorical_accuracy: 0.7977 - 508ms/epoch - 25ms/step
Epoch 427/1500
20/20 - 0s - loss: 0.5122 - categorical_accuracy: 0.8135 - val_loss: 0.5241 - val_categorical_accuracy: 0.8064 - 477ms/epoch - 24ms/step
Epoch 428/1500
20/20 - 1s - loss: 0.4843 - categorical_accuracy: 0.8221 - val_loss: 0.5013 - val_categorical_accuracy: 0.8112 - 501ms/epoch - 25ms/step
Epoch 429/1500
20/20 - 1s - loss: 0.4727 - categorical_accuracy: 0.8251 - val_loss: 0.4902 - val_categorical_accuracy: 0.8157 - 501ms/epoch - 25ms/step
Epoch 430/1500
20/20 - 0s - loss: 0.4747 - categorical_accuracy: 0.8220 - val_loss: 0.4907 - val_categorical_accuracy: 0.8150 - 486ms/epoch - 24ms/step
Epoch 431/1500
20/20 - 0s - loss: 0.4609 - categorical_accuracy: 0.8326 - val_loss: 0.5111 - val_categorical_accuracy: 0.8128 - 477ms/epoch - 24ms/step
Epoch 432/1500
20/20 - 0s - loss: 0.5108 - categorical_accuracy: 0.8134 - val_loss: 0.4799 - val_categorical_accuracy: 0.8240 - 497ms/epoch - 25ms/step
Epoch 433/1500
20/20 - 0s - loss: 0.4745 - categorical_accuracy: 0.8292 - val_loss: 0.4927 - val_categorical_accuracy: 0.8200 - 498ms/epoch - 25ms/step
Epoch 434/1500
20/20 - 0s - loss: 0.4672 - categorical_accuracy: 0.8332 - val_loss: 0.4679 - val_categorical_accuracy: 0.8310 - 491ms/epoch - 25ms/step
Epoch 435/1500
20/20 - 1s - loss: 0.4784 - categorical_accuracy: 0.8215 - val_loss: 0.5095 - val_categorical_accuracy: 0.8032 - 502ms/epoch - 25ms/step
Epoch 436/1500
20/20 - 1s - loss: 0.4805 - categorical_accuracy: 0.8184 - val_loss: 0.5073 - val_categorical_accuracy: 0.8045 - 500ms/epoch - 25ms/step
Epoch 437/1500
20/20 - 1s - loss: 0.4664 - categorical_accuracy: 0.8299 - val_loss: 0.5255 - val_categorical_accuracy: 0.8069 - 523ms/epoch - 26ms/step
Epoch 438/1500
20/20 - 1s - loss: 0.4926 - categorical_accuracy: 0.8232 - val_loss: 0.4775 - val_categorical_accuracy: 0.8257 - 506ms/epoch - 25ms/step
Epoch 439/1500
20/20 - 1s - loss: 0.4516 - categorical_accuracy: 0.8397 - val_loss: 0.4714 - val_categorical_accuracy: 0.8272 - 509ms/epoch - 25ms/step
Epoch 440/1500
20/20 - 1s - loss: 0.4753 - categorical_accuracy: 0.8218 - val_loss: 0.4933 - val_categorical_accuracy: 0.8146 - 506ms/epoch - 25ms/step
Epoch 441/1500
20/20 - 1s - loss: 0.4730 - categorical_accuracy: 0.8223 - val_loss: 0.4906 - val_categorical_accuracy: 0.8156 - 509ms/epoch - 25ms/step
Epoch 442/1500
20/20 - 1s - loss: 0.4703 - categorical_accuracy: 0.8239 - val_loss: 0.4953 - val_categorical_accuracy: 0.8138 - 516ms/epoch - 26ms/step
Epoch 443/1500
20/20 - 0s - loss: 0.5034 - categorical_accuracy: 0.8123 - val_loss: 0.5360 - val_categorical_accuracy: 0.8027 - 484ms/epoch - 24ms/step
Epoch 444/1500
20/20 - 0s - loss: 0.4811 - categorical_accuracy: 0.8267 - val_loss: 0.4853 - val_categorical_accuracy: 0.8212 - 491ms/epoch - 25ms/step
Epoch 445/1500
20/20 - 0s - loss: 0.4732 - categorical_accuracy: 0.8309 - val_loss: 0.5196 - val_categorical_accuracy: 0.8106 - 481ms/epoch - 24ms/step
Epoch 446/1500
20/20 - 0s - loss: 0.4709 - categorical_accuracy: 0.8331 - val_loss: 0.4795 - val_categorical_accuracy: 0.8227 - 472ms/epoch - 24ms/step
Epoch 447/1500
20/20 - 0s - loss: 0.4674 - categorical_accuracy: 0.8286 - val_loss: 0.4950 - val_categorical_accuracy: 0.8095 - 466ms/epoch - 23ms/step
Epoch 448/1500
20/20 - 0s - loss: 0.4651 - categorical_accuracy: 0.8251 - val_loss: 0.4898 - val_categorical_accuracy: 0.8134 - 484ms/epoch - 24ms/step
Epoch 449/1500
20/20 - 0s - loss: 0.4652 - categorical_accuracy: 0.8262 - val_loss: 0.4808 - val_categorical_accuracy: 0.8200 - 486ms/epoch - 24ms/step
Epoch 450/1500
20/20 - 0s - loss: 0.4717 - categorical_accuracy: 0.8248 - val_loss: 0.4745 - val_categorical_accuracy: 0.8278 - 485ms/epoch - 24ms/step
Epoch 451/1500
20/20 - 0s - loss: 0.4635 - categorical_accuracy: 0.8284 - val_loss: 0.4824 - val_categorical_accuracy: 0.8213 - 479ms/epoch - 24ms/step
Epoch 452/1500
20/20 - 0s - loss: 0.4993 - categorical_accuracy: 0.8170 - val_loss: 0.5265 - val_categorical_accuracy: 0.8137 - 481ms/epoch - 24ms/step
Epoch 453/1500
20/20 - 0s - loss: 0.4742 - categorical_accuracy: 0.8291 - val_loss: 0.4704 - val_categorical_accuracy: 0.8273 - 474ms/epoch - 24ms/step
Epoch 454/1500
20/20 - 0s - loss: 0.4620 - categorical_accuracy: 0.8281 - val_loss: 0.4733 - val_categorical_accuracy: 0.8295 - 476ms/epoch - 24ms/step
Epoch 455/1500
20/20 - 0s - loss: 0.4653 - categorical_accuracy: 0.8267 - val_loss: 0.4655 - val_categorical_accuracy: 0.8301 - 470ms/epoch - 24ms/step
Epoch 456/1500
20/20 - 0s - loss: 0.4523 - categorical_accuracy: 0.8342 - val_loss: 0.4769 - val_categorical_accuracy: 0.8218 - 465ms/epoch - 23ms/step
Epoch 457/1500
20/20 - 0s - loss: 0.4690 - categorical_accuracy: 0.8266 - val_loss: 0.4964 - val_categorical_accuracy: 0.8176 - 474ms/epoch - 24ms/step
Epoch 458/1500
20/20 - 0s - loss: 0.4534 - categorical_accuracy: 0.8370 - val_loss: 0.4687 - val_categorical_accuracy: 0.8261 - 482ms/epoch - 24ms/step
Epoch 459/1500
20/20 - 0s - loss: 0.4568 - categorical_accuracy: 0.8291 - val_loss: 0.4626 - val_categorical_accuracy: 0.8278 - 462ms/epoch - 23ms/step
Epoch 460/1500
20/20 - 0s - loss: 0.4560 - categorical_accuracy: 0.8299 - val_loss: 0.5099 - val_categorical_accuracy: 0.8081 - 472ms/epoch - 24ms/step
Epoch 461/1500
20/20 - 0s - loss: 0.8442 - categorical_accuracy: 0.7545 - val_loss: 0.5150 - val_categorical_accuracy: 0.8136 - 483ms/epoch - 24ms/step
Epoch 462/1500
20/20 - 0s - loss: 0.4484 - categorical_accuracy: 0.8414 - val_loss: 0.4557 - val_categorical_accuracy: 0.8385 - 476ms/epoch - 24ms/step
Epoch 463/1500
20/20 - 0s - loss: 0.4362 - categorical_accuracy: 0.8463 - val_loss: 0.4498 - val_categorical_accuracy: 0.8398 - 472ms/epoch - 24ms/step
Epoch 464/1500
20/20 - 0s - loss: 0.4318 - categorical_accuracy: 0.8473 - val_loss: 0.4465 - val_categorical_accuracy: 0.8414 - 464ms/epoch - 23ms/step
Epoch 465/1500
20/20 - 0s - loss: 0.4376 - categorical_accuracy: 0.8442 - val_loss: 0.4521 - val_categorical_accuracy: 0.8408 - 465ms/epoch - 23ms/step
Epoch 466/1500
20/20 - 0s - loss: 0.4512 - categorical_accuracy: 0.8364 - val_loss: 0.5019 - val_categorical_accuracy: 0.8177 - 478ms/epoch - 24ms/step
Epoch 467/1500
20/20 - 0s - loss: 0.4822 - categorical_accuracy: 0.8261 - val_loss: 0.4608 - val_categorical_accuracy: 0.8382 - 470ms/epoch - 24ms/step
Epoch 468/1500
20/20 - 0s - loss: 0.4495 - categorical_accuracy: 0.8350 - val_loss: 0.4541 - val_categorical_accuracy: 0.8347 - 479ms/epoch - 24ms/step
Epoch 469/1500
20/20 - 0s - loss: 0.4464 - categorical_accuracy: 0.8365 - val_loss: 0.4761 - val_categorical_accuracy: 0.8241 - 475ms/epoch - 24ms/step
Epoch 470/1500
20/20 - 0s - loss: 0.4504 - categorical_accuracy: 0.8343 - val_loss: 0.4736 - val_categorical_accuracy: 0.8219 - 488ms/epoch - 24ms/step
Epoch 471/1500
20/20 - 1s - loss: 0.4586 - categorical_accuracy: 0.8280 - val_loss: 0.4739 - val_categorical_accuracy: 0.8234 - 504ms/epoch - 25ms/step
Epoch 472/1500
20/20 - 0s - loss: 0.4502 - categorical_accuracy: 0.8363 - val_loss: 0.4966 - val_categorical_accuracy: 0.8141 - 490ms/epoch - 25ms/step
Epoch 473/1500
20/20 - 0s - loss: 0.4682 - categorical_accuracy: 0.8310 - val_loss: 0.4889 - val_categorical_accuracy: 0.8205 - 470ms/epoch - 24ms/step
Epoch 474/1500
20/20 - 0s - loss: 0.4619 - categorical_accuracy: 0.8314 - val_loss: 0.4670 - val_categorical_accuracy: 0.8249 - 474ms/epoch - 24ms/step
Epoch 475/1500
20/20 - 0s - loss: 0.4417 - categorical_accuracy: 0.8363 - val_loss: 0.4576 - val_categorical_accuracy: 0.8290 - 488ms/epoch - 24ms/step
Epoch 476/1500
20/20 - 0s - loss: 0.4427 - categorical_accuracy: 0.8355 - val_loss: 0.4785 - val_categorical_accuracy: 0.8199 - 470ms/epoch - 24ms/step
Epoch 477/1500
20/20 - 0s - loss: 0.4577 - categorical_accuracy: 0.8316 - val_loss: 0.4854 - val_categorical_accuracy: 0.8241 - 484ms/epoch - 24ms/step
Epoch 478/1500
20/20 - 0s - loss: 0.4634 - categorical_accuracy: 0.8326 - val_loss: 0.4505 - val_categorical_accuracy: 0.8402 - 478ms/epoch - 24ms/step
Epoch 479/1500
20/20 - 0s - loss: 0.4263 - categorical_accuracy: 0.8483 - val_loss: 0.4582 - val_categorical_accuracy: 0.8354 - 486ms/epoch - 24ms/step
Epoch 480/1500
20/20 - 0s - loss: 0.4700 - categorical_accuracy: 0.8271 - val_loss: 0.5210 - val_categorical_accuracy: 0.8115 - 477ms/epoch - 24ms/step
Epoch 481/1500
20/20 - 1s - loss: 0.4534 - categorical_accuracy: 0.8388 - val_loss: 0.4531 - val_categorical_accuracy: 0.8415 - 505ms/epoch - 25ms/step
Epoch 482/1500
20/20 - 0s - loss: 0.4333 - categorical_accuracy: 0.8442 - val_loss: 0.4602 - val_categorical_accuracy: 0.8292 - 486ms/epoch - 24ms/step
Epoch 483/1500
20/20 - 0s - loss: 0.4573 - categorical_accuracy: 0.8269 - val_loss: 0.4636 - val_categorical_accuracy: 0.8293 - 472ms/epoch - 24ms/step
Epoch 484/1500
20/20 - 0s - loss: 0.4334 - categorical_accuracy: 0.8411 - val_loss: 0.4686 - val_categorical_accuracy: 0.8251 - 481ms/epoch - 24ms/step
Epoch 485/1500
20/20 - 0s - loss: 0.4486 - categorical_accuracy: 0.8313 - val_loss: 0.4664 - val_categorical_accuracy: 0.8246 - 477ms/epoch - 24ms/step
Epoch 486/1500
20/20 - 0s - loss: 0.4434 - categorical_accuracy: 0.8352 - val_loss: 0.4752 - val_categorical_accuracy: 0.8236 - 484ms/epoch - 24ms/step
Epoch 487/1500
20/20 - 0s - loss: 0.4613 - categorical_accuracy: 0.8325 - val_loss: 0.4583 - val_categorical_accuracy: 0.8334 - 499ms/epoch - 25ms/step
Epoch 488/1500
20/20 - 1s - loss: 0.4628 - categorical_accuracy: 0.8343 - val_loss: 0.4687 - val_categorical_accuracy: 0.8288 - 504ms/epoch - 25ms/step
Epoch 489/1500
20/20 - 1s - loss: 0.4362 - categorical_accuracy: 0.8425 - val_loss: 0.4737 - val_categorical_accuracy: 0.8181 - 504ms/epoch - 25ms/step
Epoch 490/1500
20/20 - 0s - loss: 0.4470 - categorical_accuracy: 0.8307 - val_loss: 0.4473 - val_categorical_accuracy: 0.8345 - 489ms/epoch - 24ms/step
Epoch 491/1500
20/20 - 1s - loss: 0.4362 - categorical_accuracy: 0.8380 - val_loss: 0.4431 - val_categorical_accuracy: 0.8391 - 505ms/epoch - 25ms/step
Epoch 492/1500
20/20 - 1s - loss: 0.4277 - categorical_accuracy: 0.8434 - val_loss: 0.4459 - val_categorical_accuracy: 0.8347 - 504ms/epoch - 25ms/step
Epoch 493/1500
20/20 - 0s - loss: 0.4363 - categorical_accuracy: 0.8380 - val_loss: 0.4388 - val_categorical_accuracy: 0.8430 - 493ms/epoch - 25ms/step
Epoch 494/1500
20/20 - 1s - loss: 0.4747 - categorical_accuracy: 0.8281 - val_loss: 0.6390 - val_categorical_accuracy: 0.7708 - 500ms/epoch - 25ms/step
Epoch 495/1500
20/20 - 1s - loss: 0.4616 - categorical_accuracy: 0.8353 - val_loss: 0.4326 - val_categorical_accuracy: 0.8485 - 508ms/epoch - 25ms/step
Epoch 496/1500
20/20 - 0s - loss: 0.4141 - categorical_accuracy: 0.8537 - val_loss: 0.4536 - val_categorical_accuracy: 0.8314 - 496ms/epoch - 25ms/step
Epoch 497/1500
20/20 - 0s - loss: 0.4581 - categorical_accuracy: 0.8261 - val_loss: 0.4677 - val_categorical_accuracy: 0.8267 - 497ms/epoch - 25ms/step
Epoch 498/1500
20/20 - 0s - loss: 0.4435 - categorical_accuracy: 0.8334 - val_loss: 0.4421 - val_categorical_accuracy: 0.8376 - 496ms/epoch - 25ms/step
Epoch 499/1500
20/20 - 0s - loss: 0.4354 - categorical_accuracy: 0.8376 - val_loss: 0.4636 - val_categorical_accuracy: 0.8283 - 483ms/epoch - 24ms/step
Epoch 500/1500
20/20 - 0s - loss: 0.9382 - categorical_accuracy: 0.7602 - val_loss: 1.8027 - val_categorical_accuracy: 0.5518 - 485ms/epoch - 24ms/step
Epoch 501/1500
20/20 - 0s - loss: 0.5357 - categorical_accuracy: 0.8218 - val_loss: 0.4497 - val_categorical_accuracy: 0.8430 - 481ms/epoch - 24ms/step
Epoch 502/1500
20/20 - 0s - loss: 0.4266 - categorical_accuracy: 0.8508 - val_loss: 0.4402 - val_categorical_accuracy: 0.8434 - 467ms/epoch - 23ms/step
Epoch 503/1500
20/20 - 0s - loss: 0.4175 - categorical_accuracy: 0.8534 - val_loss: 0.4341 - val_categorical_accuracy: 0.8461 - 470ms/epoch - 24ms/step
Epoch 504/1500
20/20 - 0s - loss: 0.4119 - categorical_accuracy: 0.8549 - val_loss: 0.4258 - val_categorical_accuracy: 0.8497 - 473ms/epoch - 24ms/step
Epoch 505/1500
20/20 - 0s - loss: 0.4095 - categorical_accuracy: 0.8553 - val_loss: 0.4281 - val_categorical_accuracy: 0.8480 - 473ms/epoch - 24ms/step
Epoch 506/1500
20/20 - 0s - loss: 0.4050 - categorical_accuracy: 0.8575 - val_loss: 0.4277 - val_categorical_accuracy: 0.8498 - 470ms/epoch - 24ms/step
Epoch 507/1500
20/20 - 0s - loss: 0.4813 - categorical_accuracy: 0.8260 - val_loss: 0.4885 - val_categorical_accuracy: 0.8259 - 470ms/epoch - 24ms/step
Epoch 508/1500
20/20 - 0s - loss: 0.4124 - categorical_accuracy: 0.8536 - val_loss: 0.4323 - val_categorical_accuracy: 0.8484 - 460ms/epoch - 23ms/step
Epoch 509/1500
20/20 - 0s - loss: 0.4202 - categorical_accuracy: 0.8471 - val_loss: 0.4399 - val_categorical_accuracy: 0.8383 - 472ms/epoch - 24ms/step
Epoch 510/1500
20/20 - 0s - loss: 0.4256 - categorical_accuracy: 0.8432 - val_loss: 0.4647 - val_categorical_accuracy: 0.8251 - 470ms/epoch - 24ms/step
Epoch 511/1500
20/20 - 0s - loss: 0.4308 - categorical_accuracy: 0.8391 - val_loss: 0.4569 - val_categorical_accuracy: 0.8284 - 470ms/epoch - 24ms/step
Epoch 512/1500
20/20 - 0s - loss: 0.4336 - categorical_accuracy: 0.8392 - val_loss: 0.4438 - val_categorical_accuracy: 0.8373 - 466ms/epoch - 23ms/step
Epoch 513/1500
20/20 - 0s - loss: 0.4777 - categorical_accuracy: 0.8269 - val_loss: 0.5033 - val_categorical_accuracy: 0.8158 - 459ms/epoch - 23ms/step
Epoch 514/1500
20/20 - 0s - loss: 0.4298 - categorical_accuracy: 0.8464 - val_loss: 0.4247 - val_categorical_accuracy: 0.8459 - 481ms/epoch - 24ms/step
Epoch 515/1500
20/20 - 0s - loss: 0.4135 - categorical_accuracy: 0.8495 - val_loss: 0.4449 - val_categorical_accuracy: 0.8329 - 473ms/epoch - 24ms/step
Epoch 516/1500
20/20 - 0s - loss: 0.4249 - categorical_accuracy: 0.8419 - val_loss: 0.4497 - val_categorical_accuracy: 0.8294 - 470ms/epoch - 24ms/step
Epoch 517/1500
20/20 - 0s - loss: 0.4260 - categorical_accuracy: 0.8410 - val_loss: 0.4685 - val_categorical_accuracy: 0.8206 - 467ms/epoch - 23ms/step
Epoch 518/1500
20/20 - 0s - loss: 0.4248 - categorical_accuracy: 0.8448 - val_loss: 0.4703 - val_categorical_accuracy: 0.8270 - 470ms/epoch - 24ms/step
Epoch 519/1500
20/20 - 0s - loss: 0.4462 - categorical_accuracy: 0.8391 - val_loss: 0.4327 - val_categorical_accuracy: 0.8435 - 472ms/epoch - 24ms/step
Epoch 520/1500
20/20 - 0s - loss: 0.4068 - categorical_accuracy: 0.8534 - val_loss: 0.4475 - val_categorical_accuracy: 0.8293 - 483ms/epoch - 24ms/step
Epoch 521/1500
20/20 - 0s - loss: 0.4314 - categorical_accuracy: 0.8387 - val_loss: 0.4478 - val_categorical_accuracy: 0.8356 - 478ms/epoch - 24ms/step
Epoch 522/1500
20/20 - 0s - loss: 0.4377 - categorical_accuracy: 0.8389 - val_loss: 0.4379 - val_categorical_accuracy: 0.8434 - 475ms/epoch - 24ms/step
Epoch 523/1500
20/20 - 0s - loss: 0.4295 - categorical_accuracy: 0.8456 - val_loss: 0.4507 - val_categorical_accuracy: 0.8400 - 478ms/epoch - 24ms/step
Epoch 524/1500
20/20 - 0s - loss: 0.4334 - categorical_accuracy: 0.8454 - val_loss: 0.4699 - val_categorical_accuracy: 0.8315 - 490ms/epoch - 25ms/step
Epoch 525/1500
20/20 - 0s - loss: 0.4259 - categorical_accuracy: 0.8452 - val_loss: 0.4597 - val_categorical_accuracy: 0.8291 - 493ms/epoch - 25ms/step
Epoch 526/1500
20/20 - 0s - loss: 0.4345 - categorical_accuracy: 0.8381 - val_loss: 0.4424 - val_categorical_accuracy: 0.8350 - 479ms/epoch - 24ms/step
Epoch 527/1500
20/20 - 0s - loss: 0.4216 - categorical_accuracy: 0.8431 - val_loss: 0.4287 - val_categorical_accuracy: 0.8426 - 483ms/epoch - 24ms/step
Epoch 528/1500
20/20 - 0s - loss: 0.4131 - categorical_accuracy: 0.8478 - val_loss: 0.4187 - val_categorical_accuracy: 0.8504 - 478ms/epoch - 24ms/step
Epoch 529/1500
20/20 - 0s - loss: 0.4715 - categorical_accuracy: 0.8292 - val_loss: 0.4543 - val_categorical_accuracy: 0.8406 - 469ms/epoch - 23ms/step
Epoch 530/1500
20/20 - 0s - loss: 0.3986 - categorical_accuracy: 0.8597 - val_loss: 0.4134 - val_categorical_accuracy: 0.8511 - 486ms/epoch - 24ms/step
Epoch 531/1500
20/20 - 0s - loss: 0.4066 - categorical_accuracy: 0.8507 - val_loss: 0.4321 - val_categorical_accuracy: 0.8404 - 473ms/epoch - 24ms/step
Epoch 532/1500
20/20 - 0s - loss: 0.4216 - categorical_accuracy: 0.8436 - val_loss: 0.4519 - val_categorical_accuracy: 0.8350 - 484ms/epoch - 24ms/step
Epoch 533/1500
20/20 - 0s - loss: 0.8874 - categorical_accuracy: 0.7613 - val_loss: 0.4349 - val_categorical_accuracy: 0.8456 - 484ms/epoch - 24ms/step
Epoch 534/1500
20/20 - 1s - loss: 0.4061 - categorical_accuracy: 0.8581 - val_loss: 0.4180 - val_categorical_accuracy: 0.8533 - 510ms/epoch - 26ms/step
Epoch 535/1500
20/20 - 1s - loss: 0.3967 - categorical_accuracy: 0.8603 - val_loss: 0.4143 - val_categorical_accuracy: 0.8527 - 509ms/epoch - 25ms/step
Epoch 536/1500
20/20 - 0s - loss: 0.3929 - categorical_accuracy: 0.8613 - val_loss: 0.4072 - val_categorical_accuracy: 0.8567 - 488ms/epoch - 24ms/step
Epoch 537/1500
20/20 - 0s - loss: 0.3863 - categorical_accuracy: 0.8645 - val_loss: 0.4044 - val_categorical_accuracy: 0.8568 - 486ms/epoch - 24ms/step
Epoch 538/1500
20/20 - 0s - loss: 0.3991 - categorical_accuracy: 0.8564 - val_loss: 0.4486 - val_categorical_accuracy: 0.8289 - 478ms/epoch - 24ms/step
Epoch 539/1500
20/20 - 0s - loss: 0.4198 - categorical_accuracy: 0.8435 - val_loss: 0.4340 - val_categorical_accuracy: 0.8389 - 486ms/epoch - 24ms/step
Epoch 540/1500
20/20 - 0s - loss: 0.4758 - categorical_accuracy: 0.8237 - val_loss: 0.5295 - val_categorical_accuracy: 0.8097 - 493ms/epoch - 25ms/step
Epoch 541/1500
20/20 - 1s - loss: 0.4225 - categorical_accuracy: 0.8491 - val_loss: 0.4162 - val_categorical_accuracy: 0.8490 - 506ms/epoch - 25ms/step
Epoch 542/1500
20/20 - 0s - loss: 0.4079 - categorical_accuracy: 0.8503 - val_loss: 0.4377 - val_categorical_accuracy: 0.8375 - 489ms/epoch - 24ms/step
Epoch 543/1500
20/20 - 0s - loss: 0.4055 - categorical_accuracy: 0.8516 - val_loss: 0.4137 - val_categorical_accuracy: 0.8510 - 470ms/epoch - 24ms/step
Epoch 544/1500
20/20 - 0s - loss: 0.4060 - categorical_accuracy: 0.8508 - val_loss: 0.4082 - val_categorical_accuracy: 0.8529 - 471ms/epoch - 24ms/step
Epoch 545/1500
20/20 - 0s - loss: 0.4139 - categorical_accuracy: 0.8485 - val_loss: 0.5276 - val_categorical_accuracy: 0.8048 - 479ms/epoch - 24ms/step
Epoch 546/1500
20/20 - 0s - loss: 0.4384 - categorical_accuracy: 0.8421 - val_loss: 0.4149 - val_categorical_accuracy: 0.8489 - 472ms/epoch - 24ms/step
Epoch 547/1500
20/20 - 0s - loss: 0.3925 - categorical_accuracy: 0.8578 - val_loss: 0.4137 - val_categorical_accuracy: 0.8510 - 481ms/epoch - 24ms/step
Epoch 548/1500
20/20 - 0s - loss: 0.4164 - categorical_accuracy: 0.8444 - val_loss: 0.4423 - val_categorical_accuracy: 0.8357 - 486ms/epoch - 24ms/step
Epoch 549/1500
20/20 - 0s - loss: 0.4404 - categorical_accuracy: 0.8392 - val_loss: 0.4471 - val_categorical_accuracy: 0.8425 - 474ms/epoch - 24ms/step
Epoch 550/1500
20/20 - 0s - loss: 0.3917 - categorical_accuracy: 0.8615 - val_loss: 0.4070 - val_categorical_accuracy: 0.8553 - 470ms/epoch - 24ms/step
Epoch 551/1500
20/20 - 0s - loss: 0.4181 - categorical_accuracy: 0.8478 - val_loss: 0.4431 - val_categorical_accuracy: 0.8381 - 472ms/epoch - 24ms/step
Epoch 552/1500
20/20 - 0s - loss: 0.4036 - categorical_accuracy: 0.8517 - val_loss: 0.4149 - val_categorical_accuracy: 0.8462 - 471ms/epoch - 24ms/step
Epoch 553/1500
20/20 - 0s - loss: 0.4076 - categorical_accuracy: 0.8495 - val_loss: 0.4596 - val_categorical_accuracy: 0.8243 - 466ms/epoch - 23ms/step
Epoch 554/1500
20/20 - 0s - loss: 0.4295 - categorical_accuracy: 0.8430 - val_loss: 0.4663 - val_categorical_accuracy: 0.8328 - 460ms/epoch - 23ms/step
Epoch 555/1500
20/20 - 0s - loss: 0.4121 - categorical_accuracy: 0.8552 - val_loss: 0.4079 - val_categorical_accuracy: 0.8530 - 457ms/epoch - 23ms/step
Epoch 556/1500
20/20 - 0s - loss: 0.3897 - categorical_accuracy: 0.8627 - val_loss: 0.4156 - val_categorical_accuracy: 0.8498 - 467ms/epoch - 23ms/step
Epoch 557/1500
20/20 - 0s - loss: 0.4142 - categorical_accuracy: 0.8530 - val_loss: 0.4435 - val_categorical_accuracy: 0.8395 - 456ms/epoch - 23ms/step
Epoch 558/1500
20/20 - 0s - loss: 0.4202 - categorical_accuracy: 0.8435 - val_loss: 0.4351 - val_categorical_accuracy: 0.8377 - 458ms/epoch - 23ms/step
Epoch 559/1500
20/20 - 0s - loss: 0.4081 - categorical_accuracy: 0.8479 - val_loss: 0.4167 - val_categorical_accuracy: 0.8469 - 472ms/epoch - 24ms/step
Epoch 560/1500
20/20 - 0s - loss: 0.3988 - categorical_accuracy: 0.8531 - val_loss: 0.4251 - val_categorical_accuracy: 0.8470 - 465ms/epoch - 23ms/step
Epoch 561/1500
20/20 - 0s - loss: 0.4175 - categorical_accuracy: 0.8493 - val_loss: 0.4126 - val_categorical_accuracy: 0.8553 - 474ms/epoch - 24ms/step
Epoch 562/1500
20/20 - 0s - loss: 0.3937 - categorical_accuracy: 0.8603 - val_loss: 0.4242 - val_categorical_accuracy: 0.8463 - 492ms/epoch - 25ms/step
Epoch 563/1500
20/20 - 0s - loss: 0.4021 - categorical_accuracy: 0.8534 - val_loss: 0.4241 - val_categorical_accuracy: 0.8402 - 488ms/epoch - 24ms/step
Epoch 564/1500
20/20 - 0s - loss: 0.4113 - categorical_accuracy: 0.8454 - val_loss: 0.4148 - val_categorical_accuracy: 0.8476 - 490ms/epoch - 25ms/step
Epoch 565/1500
20/20 - 1s - loss: 0.4046 - categorical_accuracy: 0.8500 - val_loss: 0.4224 - val_categorical_accuracy: 0.8414 - 501ms/epoch - 25ms/step
Epoch 566/1500
20/20 - 1s - loss: 0.3904 - categorical_accuracy: 0.8578 - val_loss: 0.4094 - val_categorical_accuracy: 0.8552 - 759ms/epoch - 38ms/step
Epoch 567/1500
20/20 - 0s - loss: 0.4306 - categorical_accuracy: 0.8439 - val_loss: 0.5195 - val_categorical_accuracy: 0.8137 - 499ms/epoch - 25ms/step
Epoch 568/1500
20/20 - 0s - loss: 0.4142 - categorical_accuracy: 0.8524 - val_loss: 0.4112 - val_categorical_accuracy: 0.8528 - 473ms/epoch - 24ms/step
Epoch 569/1500
20/20 - 0s - loss: 0.4020 - categorical_accuracy: 0.8536 - val_loss: 0.4352 - val_categorical_accuracy: 0.8371 - 490ms/epoch - 25ms/step
Epoch 570/1500
20/20 - 0s - loss: 0.4034 - categorical_accuracy: 0.8509 - val_loss: 0.4268 - val_categorical_accuracy: 0.8424 - 482ms/epoch - 24ms/step
Epoch 571/1500
20/20 - 0s - loss: 0.3886 - categorical_accuracy: 0.8597 - val_loss: 0.4121 - val_categorical_accuracy: 0.8509 - 488ms/epoch - 24ms/step
Epoch 572/1500
20/20 - 0s - loss: 0.4001 - categorical_accuracy: 0.8534 - val_loss: 0.4205 - val_categorical_accuracy: 0.8498 - 479ms/epoch - 24ms/step
Epoch 573/1500
20/20 - 0s - loss: 0.4017 - categorical_accuracy: 0.8559 - val_loss: 0.4373 - val_categorical_accuracy: 0.8422 - 491ms/epoch - 25ms/step
Epoch 574/1500
20/20 - 0s - loss: 0.4113 - categorical_accuracy: 0.8508 - val_loss: 0.4131 - val_categorical_accuracy: 0.8542 - 481ms/epoch - 24ms/step
Epoch 575/1500
20/20 - 0s - loss: 0.4152 - categorical_accuracy: 0.8522 - val_loss: 0.4537 - val_categorical_accuracy: 0.8385 - 480ms/epoch - 24ms/step
Epoch 576/1500
20/20 - 0s - loss: 0.4036 - categorical_accuracy: 0.8529 - val_loss: 0.4149 - val_categorical_accuracy: 0.8463 - 472ms/epoch - 24ms/step
Epoch 577/1500
20/20 - 0s - loss: 0.3865 - categorical_accuracy: 0.8594 - val_loss: 0.4010 - val_categorical_accuracy: 0.8532 - 483ms/epoch - 24ms/step
Epoch 578/1500
20/20 - 0s - loss: 0.3898 - categorical_accuracy: 0.8573 - val_loss: 0.4270 - val_categorical_accuracy: 0.8382 - 491ms/epoch - 25ms/step
Epoch 579/1500
20/20 - 0s - loss: 0.3955 - categorical_accuracy: 0.8545 - val_loss: 0.4323 - val_categorical_accuracy: 0.8406 - 489ms/epoch - 24ms/step
Epoch 580/1500
20/20 - 0s - loss: 0.4338 - categorical_accuracy: 0.8452 - val_loss: 0.4547 - val_categorical_accuracy: 0.8376 - 473ms/epoch - 24ms/step
Epoch 581/1500
20/20 - 0s - loss: 0.3927 - categorical_accuracy: 0.8623 - val_loss: 0.3992 - val_categorical_accuracy: 0.8554 - 483ms/epoch - 24ms/step
Epoch 582/1500
20/20 - 0s - loss: 0.3864 - categorical_accuracy: 0.8589 - val_loss: 0.4280 - val_categorical_accuracy: 0.8407 - 471ms/epoch - 24ms/step
Epoch 583/1500
20/20 - 0s - loss: 0.4040 - categorical_accuracy: 0.8486 - val_loss: 0.3983 - val_categorical_accuracy: 0.8551 - 496ms/epoch - 25ms/step
Epoch 584/1500
20/20 - 1s - loss: 0.3811 - categorical_accuracy: 0.8611 - val_loss: 0.3963 - val_categorical_accuracy: 0.8567 - 507ms/epoch - 25ms/step
Epoch 585/1500
20/20 - 1s - loss: 0.3820 - categorical_accuracy: 0.8600 - val_loss: 0.3986 - val_categorical_accuracy: 0.8582 - 510ms/epoch - 26ms/step
Epoch 586/1500
20/20 - 1s - loss: 0.4751 - categorical_accuracy: 0.8393 - val_loss: 3.5043 - val_categorical_accuracy: 0.5563 - 500ms/epoch - 25ms/step
Epoch 587/1500
20/20 - 1s - loss: 0.9168 - categorical_accuracy: 0.7869 - val_loss: 0.4056 - val_categorical_accuracy: 0.8585 - 514ms/epoch - 26ms/step
Epoch 588/1500
20/20 - 1s - loss: 0.3799 - categorical_accuracy: 0.8678 - val_loss: 0.3969 - val_categorical_accuracy: 0.8614 - 506ms/epoch - 25ms/step
Epoch 589/1500
20/20 - 1s - loss: 0.3709 - categorical_accuracy: 0.8714 - val_loss: 0.3873 - val_categorical_accuracy: 0.8639 - 528ms/epoch - 26ms/step
Epoch 590/1500
20/20 - 1s - loss: 0.3669 - categorical_accuracy: 0.8713 - val_loss: 0.3860 - val_categorical_accuracy: 0.8624 - 511ms/epoch - 26ms/step
Epoch 591/1500
20/20 - 1s - loss: 0.3661 - categorical_accuracy: 0.8715 - val_loss: 0.4014 - val_categorical_accuracy: 0.8599 - 511ms/epoch - 26ms/step
Epoch 592/1500
20/20 - 1s - loss: 0.4049 - categorical_accuracy: 0.8559 - val_loss: 0.4688 - val_categorical_accuracy: 0.8330 - 500ms/epoch - 25ms/step
Epoch 593/1500
20/20 - 1s - loss: 0.3996 - categorical_accuracy: 0.8586 - val_loss: 0.3835 - val_categorical_accuracy: 0.8651 - 501ms/epoch - 25ms/step
Epoch 594/1500
20/20 - 0s - loss: 0.3678 - categorical_accuracy: 0.8692 - val_loss: 0.3991 - val_categorical_accuracy: 0.8530 - 488ms/epoch - 24ms/step
Epoch 595/1500
20/20 - 0s - loss: 0.3920 - categorical_accuracy: 0.8541 - val_loss: 0.3873 - val_categorical_accuracy: 0.8600 - 488ms/epoch - 24ms/step
Epoch 596/1500
20/20 - 0s - loss: 0.3877 - categorical_accuracy: 0.8568 - val_loss: 0.4249 - val_categorical_accuracy: 0.8369 - 486ms/epoch - 24ms/step
Epoch 597/1500
20/20 - 0s - loss: 0.3896 - categorical_accuracy: 0.8564 - val_loss: 0.3921 - val_categorical_accuracy: 0.8573 - 486ms/epoch - 24ms/step
Epoch 598/1500
20/20 - 0s - loss: 0.3895 - categorical_accuracy: 0.8577 - val_loss: 0.4045 - val_categorical_accuracy: 0.8494 - 474ms/epoch - 24ms/step
Epoch 599/1500
20/20 - 0s - loss: 0.3823 - categorical_accuracy: 0.8623 - val_loss: 0.4223 - val_categorical_accuracy: 0.8467 - 476ms/epoch - 24ms/step
Epoch 600/1500
20/20 - 0s - loss: 0.4637 - categorical_accuracy: 0.8353 - val_loss: 0.4047 - val_categorical_accuracy: 0.8538 - 482ms/epoch - 24ms/step
Epoch 601/1500
20/20 - 0s - loss: 0.3658 - categorical_accuracy: 0.8700 - val_loss: 0.3819 - val_categorical_accuracy: 0.8643 - 479ms/epoch - 24ms/step
Epoch 602/1500
20/20 - 0s - loss: 0.3580 - categorical_accuracy: 0.8739 - val_loss: 0.3957 - val_categorical_accuracy: 0.8567 - 461ms/epoch - 23ms/step
Epoch 603/1500
20/20 - 0s - loss: 0.3911 - categorical_accuracy: 0.8549 - val_loss: 0.4289 - val_categorical_accuracy: 0.8402 - 468ms/epoch - 23ms/step
Epoch 604/1500
20/20 - 0s - loss: 0.3935 - categorical_accuracy: 0.8548 - val_loss: 0.4032 - val_categorical_accuracy: 0.8519 - 481ms/epoch - 24ms/step
Epoch 605/1500
20/20 - 0s - loss: 0.3793 - categorical_accuracy: 0.8611 - val_loss: 0.4157 - val_categorical_accuracy: 0.8471 - 481ms/epoch - 24ms/step
Epoch 606/1500
20/20 - 0s - loss: 0.3820 - categorical_accuracy: 0.8598 - val_loss: 0.4056 - val_categorical_accuracy: 0.8519 - 480ms/epoch - 24ms/step
Epoch 607/1500
20/20 - 0s - loss: 0.3953 - categorical_accuracy: 0.8548 - val_loss: 0.4625 - val_categorical_accuracy: 0.8314 - 488ms/epoch - 24ms/step
Epoch 608/1500
20/20 - 0s - loss: 0.4580 - categorical_accuracy: 0.8350 - val_loss: 0.3740 - val_categorical_accuracy: 0.8688 - 488ms/epoch - 24ms/step
Epoch 609/1500
20/20 - 0s - loss: 0.3516 - categorical_accuracy: 0.8771 - val_loss: 0.3740 - val_categorical_accuracy: 0.8666 - 484ms/epoch - 24ms/step
Epoch 610/1500
20/20 - 0s - loss: 0.3603 - categorical_accuracy: 0.8725 - val_loss: 0.3807 - val_categorical_accuracy: 0.8630 - 488ms/epoch - 24ms/step
Epoch 611/1500
20/20 - 0s - loss: 0.3756 - categorical_accuracy: 0.8631 - val_loss: 0.4063 - val_categorical_accuracy: 0.8510 - 490ms/epoch - 25ms/step
Epoch 612/1500
20/20 - 0s - loss: 0.3896 - categorical_accuracy: 0.8548 - val_loss: 0.3954 - val_categorical_accuracy: 0.8546 - 482ms/epoch - 24ms/step
Epoch 613/1500
20/20 - 0s - loss: 0.3786 - categorical_accuracy: 0.8593 - val_loss: 0.4007 - val_categorical_accuracy: 0.8507 - 474ms/epoch - 24ms/step
Epoch 614/1500
20/20 - 0s - loss: 0.3883 - categorical_accuracy: 0.8561 - val_loss: 0.3853 - val_categorical_accuracy: 0.8621 - 486ms/epoch - 24ms/step
Epoch 615/1500
20/20 - 0s - loss: 0.3826 - categorical_accuracy: 0.8620 - val_loss: 0.4615 - val_categorical_accuracy: 0.8346 - 487ms/epoch - 24ms/step
Epoch 616/1500
20/20 - 0s - loss: 0.4420 - categorical_accuracy: 0.8421 - val_loss: 0.3754 - val_categorical_accuracy: 0.8702 - 497ms/epoch - 25ms/step
Epoch 617/1500
20/20 - 1s - loss: 0.3481 - categorical_accuracy: 0.8787 - val_loss: 0.3693 - val_categorical_accuracy: 0.8677 - 514ms/epoch - 26ms/step
Epoch 618/1500
20/20 - 0s - loss: 0.3602 - categorical_accuracy: 0.8698 - val_loss: 0.4109 - val_categorical_accuracy: 0.8429 - 494ms/epoch - 25ms/step
Epoch 619/1500
20/20 - 0s - loss: 0.3820 - categorical_accuracy: 0.8580 - val_loss: 0.3850 - val_categorical_accuracy: 0.8595 - 486ms/epoch - 24ms/step
Epoch 620/1500
20/20 - 0s - loss: 0.3761 - categorical_accuracy: 0.8622 - val_loss: 0.4227 - val_categorical_accuracy: 0.8418 - 493ms/epoch - 25ms/step
Epoch 621/1500
20/20 - 0s - loss: 0.4063 - categorical_accuracy: 0.8486 - val_loss: 0.3805 - val_categorical_accuracy: 0.8618 - 486ms/epoch - 24ms/step
Epoch 622/1500
20/20 - 0s - loss: 0.3769 - categorical_accuracy: 0.8620 - val_loss: 0.4102 - val_categorical_accuracy: 0.8519 - 487ms/epoch - 24ms/step
Epoch 623/1500
20/20 - 0s - loss: 0.4161 - categorical_accuracy: 0.8498 - val_loss: 0.4187 - val_categorical_accuracy: 0.8493 - 481ms/epoch - 24ms/step
Epoch 624/1500
20/20 - 0s - loss: 0.3589 - categorical_accuracy: 0.8732 - val_loss: 0.3739 - val_categorical_accuracy: 0.8650 - 484ms/epoch - 24ms/step
Epoch 625/1500
20/20 - 0s - loss: 0.3669 - categorical_accuracy: 0.8663 - val_loss: 0.4009 - val_categorical_accuracy: 0.8468 - 490ms/epoch - 25ms/step
Epoch 626/1500
20/20 - 0s - loss: 0.3679 - categorical_accuracy: 0.8643 - val_loss: 0.3986 - val_categorical_accuracy: 0.8481 - 498ms/epoch - 25ms/step
Epoch 627/1500
20/20 - 0s - loss: 0.3885 - categorical_accuracy: 0.8535 - val_loss: 0.3812 - val_categorical_accuracy: 0.8614 - 488ms/epoch - 24ms/step
Epoch 628/1500
20/20 - 0s - loss: 0.3664 - categorical_accuracy: 0.8669 - val_loss: 0.3826 - val_categorical_accuracy: 0.8593 - 486ms/epoch - 24ms/step
Epoch 629/1500
20/20 - 0s - loss: 0.3739 - categorical_accuracy: 0.8653 - val_loss: 0.4015 - val_categorical_accuracy: 0.8508 - 483ms/epoch - 24ms/step
Epoch 630/1500
20/20 - 0s - loss: 0.3750 - categorical_accuracy: 0.8629 - val_loss: 0.3993 - val_categorical_accuracy: 0.8536 - 485ms/epoch - 24ms/step
Epoch 631/1500
20/20 - 0s - loss: 0.4351 - categorical_accuracy: 0.8405 - val_loss: 0.4937 - val_categorical_accuracy: 0.8254 - 482ms/epoch - 24ms/step
Epoch 632/1500
20/20 - 0s - loss: 0.3736 - categorical_accuracy: 0.8700 - val_loss: 0.3619 - val_categorical_accuracy: 0.8729 - 489ms/epoch - 24ms/step
Epoch 633/1500
20/20 - 0s - loss: 0.3544 - categorical_accuracy: 0.8733 - val_loss: 0.3944 - val_categorical_accuracy: 0.8506 - 473ms/epoch - 24ms/step
Epoch 634/1500
20/20 - 0s - loss: 0.3783 - categorical_accuracy: 0.8580 - val_loss: 0.3869 - val_categorical_accuracy: 0.8564 - 482ms/epoch - 24ms/step
Epoch 635/1500
20/20 - 1s - loss: 0.3598 - categorical_accuracy: 0.8687 - val_loss: 0.3782 - val_categorical_accuracy: 0.8619 - 533ms/epoch - 27ms/step
Epoch 636/1500
20/20 - 1s - loss: 0.3839 - categorical_accuracy: 0.8579 - val_loss: 0.4099 - val_categorical_accuracy: 0.8472 - 520ms/epoch - 26ms/step
Epoch 637/1500
20/20 - 1s - loss: 0.3669 - categorical_accuracy: 0.8687 - val_loss: 0.3740 - val_categorical_accuracy: 0.8644 - 501ms/epoch - 25ms/step
Epoch 638/1500
20/20 - 1s - loss: 0.3644 - categorical_accuracy: 0.8676 - val_loss: 0.3901 - val_categorical_accuracy: 0.8573 - 516ms/epoch - 26ms/step
Epoch 639/1500
20/20 - 0s - loss: 0.3683 - categorical_accuracy: 0.8655 - val_loss: 0.3787 - val_categorical_accuracy: 0.8603 - 490ms/epoch - 25ms/step
Epoch 640/1500
20/20 - 0s - loss: 0.3582 - categorical_accuracy: 0.8707 - val_loss: 0.3889 - val_categorical_accuracy: 0.8558 - 495ms/epoch - 25ms/step
Epoch 641/1500
20/20 - 0s - loss: 0.3966 - categorical_accuracy: 0.8579 - val_loss: 0.5753 - val_categorical_accuracy: 0.7979 - 498ms/epoch - 25ms/step
Epoch 642/1500
20/20 - 0s - loss: 0.4451 - categorical_accuracy: 0.8442 - val_loss: 0.3584 - val_categorical_accuracy: 0.8737 - 485ms/epoch - 24ms/step
Epoch 643/1500
20/20 - 0s - loss: 0.3385 - categorical_accuracy: 0.8820 - val_loss: 0.3776 - val_categorical_accuracy: 0.8625 - 465ms/epoch - 23ms/step
Epoch 644/1500
20/20 - 0s - loss: 0.3757 - categorical_accuracy: 0.8597 - val_loss: 0.4024 - val_categorical_accuracy: 0.8518 - 472ms/epoch - 24ms/step
Epoch 645/1500
20/20 - 0s - loss: 0.3648 - categorical_accuracy: 0.8667 - val_loss: 0.3995 - val_categorical_accuracy: 0.8507 - 478ms/epoch - 24ms/step
Epoch 646/1500
20/20 - 0s - loss: 0.3606 - categorical_accuracy: 0.8682 - val_loss: 0.3634 - val_categorical_accuracy: 0.8701 - 472ms/epoch - 24ms/step
Epoch 647/1500
20/20 - 0s - loss: 0.3419 - categorical_accuracy: 0.8781 - val_loss: 0.3781 - val_categorical_accuracy: 0.8615 - 472ms/epoch - 24ms/step
Epoch 648/1500
20/20 - 0s - loss: 0.3730 - categorical_accuracy: 0.8603 - val_loss: 0.3967 - val_categorical_accuracy: 0.8532 - 474ms/epoch - 24ms/step
Epoch 649/1500
20/20 - 0s - loss: 0.3951 - categorical_accuracy: 0.8542 - val_loss: 0.4037 - val_categorical_accuracy: 0.8538 - 472ms/epoch - 24ms/step
Epoch 650/1500
20/20 - 0s - loss: 0.3604 - categorical_accuracy: 0.8713 - val_loss: 0.3821 - val_categorical_accuracy: 0.8621 - 486ms/epoch - 24ms/step
Epoch 651/1500
20/20 - 0s - loss: 0.4551 - categorical_accuracy: 0.8360 - val_loss: 0.4037 - val_categorical_accuracy: 0.8561 - 490ms/epoch - 25ms/step
Epoch 652/1500
20/20 - 0s - loss: 0.3402 - categorical_accuracy: 0.8817 - val_loss: 0.3615 - val_categorical_accuracy: 0.8723 - 488ms/epoch - 24ms/step
Epoch 653/1500
20/20 - 0s - loss: 0.3429 - categorical_accuracy: 0.8783 - val_loss: 0.3596 - val_categorical_accuracy: 0.8744 - 484ms/epoch - 24ms/step
Epoch 654/1500
20/20 - 1s - loss: 0.3666 - categorical_accuracy: 0.8633 - val_loss: 0.4148 - val_categorical_accuracy: 0.8434 - 506ms/epoch - 25ms/step
Epoch 655/1500
20/20 - 1s - loss: 0.3651 - categorical_accuracy: 0.8665 - val_loss: 0.3612 - val_categorical_accuracy: 0.8707 - 502ms/epoch - 25ms/step
Epoch 656/1500
20/20 - 0s - loss: 0.3449 - categorical_accuracy: 0.8766 - val_loss: 0.3898 - val_categorical_accuracy: 0.8562 - 487ms/epoch - 24ms/step
Epoch 657/1500
20/20 - 0s - loss: 0.4013 - categorical_accuracy: 0.8499 - val_loss: 0.4038 - val_categorical_accuracy: 0.8556 - 487ms/epoch - 24ms/step
Epoch 658/1500
20/20 - 0s - loss: 0.3627 - categorical_accuracy: 0.8699 - val_loss: 0.3696 - val_categorical_accuracy: 0.8667 - 462ms/epoch - 23ms/step
Epoch 659/1500
20/20 - 0s - loss: 0.3542 - categorical_accuracy: 0.8717 - val_loss: 0.3726 - val_categorical_accuracy: 0.8648 - 472ms/epoch - 24ms/step
Epoch 660/1500
20/20 - 0s - loss: 0.3566 - categorical_accuracy: 0.8699 - val_loss: 0.4118 - val_categorical_accuracy: 0.8477 - 481ms/epoch - 24ms/step
Epoch 661/1500
20/20 - 0s - loss: 0.4669 - categorical_accuracy: 0.8332 - val_loss: 0.3650 - val_categorical_accuracy: 0.8703 - 471ms/epoch - 24ms/step
Epoch 662/1500
20/20 - 0s - loss: 0.3311 - categorical_accuracy: 0.8851 - val_loss: 0.3585 - val_categorical_accuracy: 0.8750 - 471ms/epoch - 24ms/step
Epoch 663/1500
20/20 - 0s - loss: 0.3506 - categorical_accuracy: 0.8737 - val_loss: 0.3854 - val_categorical_accuracy: 0.8622 - 480ms/epoch - 24ms/step
Epoch 664/1500
20/20 - 0s - loss: 0.3551 - categorical_accuracy: 0.8725 - val_loss: 0.3814 - val_categorical_accuracy: 0.8645 - 484ms/epoch - 24ms/step
Epoch 665/1500
20/20 - 0s - loss: 0.3464 - categorical_accuracy: 0.8757 - val_loss: 0.3578 - val_categorical_accuracy: 0.8733 - 487ms/epoch - 24ms/step
Epoch 666/1500
20/20 - 0s - loss: 0.3664 - categorical_accuracy: 0.8661 - val_loss: 0.3979 - val_categorical_accuracy: 0.8520 - 487ms/epoch - 24ms/step
Epoch 667/1500
20/20 - 0s - loss: 0.3731 - categorical_accuracy: 0.8637 - val_loss: 0.3631 - val_categorical_accuracy: 0.8690 - 475ms/epoch - 24ms/step
Epoch 668/1500
20/20 - 0s - loss: 0.3532 - categorical_accuracy: 0.8710 - val_loss: 0.4092 - val_categorical_accuracy: 0.8415 - 480ms/epoch - 24ms/step
Epoch 669/1500
20/20 - 0s - loss: 0.3826 - categorical_accuracy: 0.8564 - val_loss: 0.4117 - val_categorical_accuracy: 0.8526 - 468ms/epoch - 23ms/step
Epoch 670/1500
20/20 - 0s - loss: 0.4377 - categorical_accuracy: 0.8445 - val_loss: 0.3537 - val_categorical_accuracy: 0.8773 - 482ms/epoch - 24ms/step
Epoch 671/1500
20/20 - 0s - loss: 0.3242 - categorical_accuracy: 0.8882 - val_loss: 0.3442 - val_categorical_accuracy: 0.8786 - 479ms/epoch - 24ms/step
Epoch 672/1500
20/20 - 0s - loss: 0.3565 - categorical_accuracy: 0.8698 - val_loss: 0.3839 - val_categorical_accuracy: 0.8559 - 476ms/epoch - 24ms/step
Epoch 673/1500
20/20 - 0s - loss: 0.3516 - categorical_accuracy: 0.8720 - val_loss: 0.3933 - val_categorical_accuracy: 0.8524 - 482ms/epoch - 24ms/step
Epoch 674/1500
20/20 - 0s - loss: 0.3633 - categorical_accuracy: 0.8664 - val_loss: 0.3765 - val_categorical_accuracy: 0.8619 - 492ms/epoch - 25ms/step
Epoch 675/1500
20/20 - 0s - loss: 0.3530 - categorical_accuracy: 0.8717 - val_loss: 0.4139 - val_categorical_accuracy: 0.8401 - 473ms/epoch - 24ms/step
Epoch 676/1500
20/20 - 0s - loss: 0.3694 - categorical_accuracy: 0.8624 - val_loss: 0.3704 - val_categorical_accuracy: 0.8652 - 477ms/epoch - 24ms/step
Epoch 677/1500
20/20 - 0s - loss: 0.3581 - categorical_accuracy: 0.8717 - val_loss: 0.3842 - val_categorical_accuracy: 0.8629 - 482ms/epoch - 24ms/step
Epoch 678/1500
20/20 - 0s - loss: 0.3509 - categorical_accuracy: 0.8725 - val_loss: 0.4009 - val_categorical_accuracy: 0.8510 - 488ms/epoch - 24ms/step
Epoch 679/1500
20/20 - 0s - loss: 0.3682 - categorical_accuracy: 0.8622 - val_loss: 0.3762 - val_categorical_accuracy: 0.8603 - 490ms/epoch - 25ms/step
Epoch 680/1500
20/20 - 0s - loss: 0.3339 - categorical_accuracy: 0.8815 - val_loss: 0.3669 - val_categorical_accuracy: 0.8708 - 495ms/epoch - 25ms/step
Epoch 681/1500
20/20 - 1s - loss: 0.3417 - categorical_accuracy: 0.8781 - val_loss: 0.3619 - val_categorical_accuracy: 0.8706 - 506ms/epoch - 25ms/step
Epoch 682/1500
20/20 - 0s - loss: 0.3396 - categorical_accuracy: 0.8784 - val_loss: 0.3737 - val_categorical_accuracy: 0.8618 - 499ms/epoch - 25ms/step
Epoch 683/1500
20/20 - 0s - loss: 0.3593 - categorical_accuracy: 0.8672 - val_loss: 0.3699 - val_categorical_accuracy: 0.8625 - 491ms/epoch - 25ms/step
Epoch 684/1500
20/20 - 0s - loss: 0.3665 - categorical_accuracy: 0.8655 - val_loss: 0.4832 - val_categorical_accuracy: 0.8229 - 493ms/epoch - 25ms/step
Epoch 685/1500
20/20 - 0s - loss: 0.4669 - categorical_accuracy: 0.8382 - val_loss: 0.3440 - val_categorical_accuracy: 0.8797 - 494ms/epoch - 25ms/step
Epoch 686/1500
20/20 - 0s - loss: 0.3201 - categorical_accuracy: 0.8895 - val_loss: 0.3406 - val_categorical_accuracy: 0.8812 - 499ms/epoch - 25ms/step
Epoch 687/1500
20/20 - 0s - loss: 0.3299 - categorical_accuracy: 0.8850 - val_loss: 0.3489 - val_categorical_accuracy: 0.8778 - 489ms/epoch - 24ms/step
Epoch 688/1500
20/20 - 0s - loss: 0.3242 - categorical_accuracy: 0.8863 - val_loss: 0.3505 - val_categorical_accuracy: 0.8759 - 487ms/epoch - 24ms/step
Epoch 689/1500
20/20 - 1s - loss: 0.3430 - categorical_accuracy: 0.8760 - val_loss: 0.4028 - val_categorical_accuracy: 0.8504 - 505ms/epoch - 25ms/step
Epoch 690/1500
20/20 - 1s - loss: 0.3804 - categorical_accuracy: 0.8555 - val_loss: 0.3859 - val_categorical_accuracy: 0.8557 - 502ms/epoch - 25ms/step
Epoch 691/1500
20/20 - 1s - loss: 0.3513 - categorical_accuracy: 0.8711 - val_loss: 0.3670 - val_categorical_accuracy: 0.8688 - 518ms/epoch - 26ms/step
Epoch 692/1500
20/20 - 1s - loss: 0.3510 - categorical_accuracy: 0.8716 - val_loss: 0.3782 - val_categorical_accuracy: 0.8641 - 511ms/epoch - 26ms/step
Epoch 693/1500
20/20 - 1s - loss: 0.3362 - categorical_accuracy: 0.8798 - val_loss: 0.3554 - val_categorical_accuracy: 0.8726 - 520ms/epoch - 26ms/step
Epoch 694/1500
20/20 - 1s - loss: 0.3589 - categorical_accuracy: 0.8692 - val_loss: 0.4368 - val_categorical_accuracy: 0.8364 - 520ms/epoch - 26ms/step
Epoch 695/1500
20/20 - 0s - loss: 0.3820 - categorical_accuracy: 0.8598 - val_loss: 0.4060 - val_categorical_accuracy: 0.8500 - 497ms/epoch - 25ms/step
Epoch 696/1500
20/20 - 1s - loss: 0.3395 - categorical_accuracy: 0.8788 - val_loss: 0.3748 - val_categorical_accuracy: 0.8584 - 514ms/epoch - 26ms/step
Epoch 697/1500
20/20 - 0s - loss: 0.3353 - categorical_accuracy: 0.8799 - val_loss: 0.3453 - val_categorical_accuracy: 0.8794 - 498ms/epoch - 25ms/step
Epoch 698/1500
20/20 - 0s - loss: 0.3398 - categorical_accuracy: 0.8791 - val_loss: 0.3744 - val_categorical_accuracy: 0.8617 - 492ms/epoch - 25ms/step
Epoch 699/1500
20/20 - 1s - loss: 0.3642 - categorical_accuracy: 0.8633 - val_loss: 0.3970 - val_categorical_accuracy: 0.8508 - 504ms/epoch - 25ms/step
Epoch 700/1500
20/20 - 1s - loss: 0.3571 - categorical_accuracy: 0.8670 - val_loss: 0.3809 - val_categorical_accuracy: 0.8582 - 502ms/epoch - 25ms/step
Epoch 701/1500
20/20 - 0s - loss: 0.3715 - categorical_accuracy: 0.8665 - val_loss: 0.4671 - val_categorical_accuracy: 0.8364 - 477ms/epoch - 24ms/step
Epoch 702/1500
20/20 - 0s - loss: 0.4069 - categorical_accuracy: 0.8563 - val_loss: 0.3457 - val_categorical_accuracy: 0.8756 - 463ms/epoch - 23ms/step
Epoch 703/1500
20/20 - 0s - loss: 0.3307 - categorical_accuracy: 0.8812 - val_loss: 0.3490 - val_categorical_accuracy: 0.8760 - 494ms/epoch - 25ms/step
Epoch 704/1500
20/20 - 0s - loss: 0.3219 - categorical_accuracy: 0.8871 - val_loss: 0.3701 - val_categorical_accuracy: 0.8686 - 487ms/epoch - 24ms/step
Epoch 705/1500
20/20 - 0s - loss: 0.3441 - categorical_accuracy: 0.8759 - val_loss: 0.3751 - val_categorical_accuracy: 0.8659 - 484ms/epoch - 24ms/step
Epoch 706/1500
20/20 - 0s - loss: 0.3483 - categorical_accuracy: 0.8764 - val_loss: 0.5212 - val_categorical_accuracy: 0.8146 - 496ms/epoch - 25ms/step
Epoch 707/1500
20/20 - 0s - loss: 0.4393 - categorical_accuracy: 0.8449 - val_loss: 0.3421 - val_categorical_accuracy: 0.8794 - 474ms/epoch - 24ms/step
Epoch 708/1500
20/20 - 0s - loss: 0.3278 - categorical_accuracy: 0.8829 - val_loss: 0.3557 - val_categorical_accuracy: 0.8686 - 460ms/epoch - 23ms/step
Epoch 709/1500
20/20 - 0s - loss: 0.3421 - categorical_accuracy: 0.8747 - val_loss: 0.3885 - val_categorical_accuracy: 0.8519 - 467ms/epoch - 23ms/step
Epoch 710/1500
20/20 - 0s - loss: 0.3480 - categorical_accuracy: 0.8722 - val_loss: 0.3607 - val_categorical_accuracy: 0.8655 - 465ms/epoch - 23ms/step
Epoch 711/1500
20/20 - 0s - loss: 0.3408 - categorical_accuracy: 0.8765 - val_loss: 0.3431 - val_categorical_accuracy: 0.8773 - 474ms/epoch - 24ms/step
Epoch 712/1500
20/20 - 0s - loss: 0.3232 - categorical_accuracy: 0.8861 - val_loss: 0.3511 - val_categorical_accuracy: 0.8760 - 468ms/epoch - 23ms/step
Epoch 713/1500
20/20 - 0s - loss: 0.3475 - categorical_accuracy: 0.8738 - val_loss: 0.3592 - val_categorical_accuracy: 0.8686 - 488ms/epoch - 24ms/step
Epoch 714/1500
20/20 - 0s - loss: 0.3448 - categorical_accuracy: 0.8732 - val_loss: 0.3823 - val_categorical_accuracy: 0.8562 - 492ms/epoch - 25ms/step
Epoch 715/1500
20/20 - 0s - loss: 0.3498 - categorical_accuracy: 0.8718 - val_loss: 0.4118 - val_categorical_accuracy: 0.8408 - 488ms/epoch - 24ms/step
Epoch 716/1500
20/20 - 0s - loss: 0.3608 - categorical_accuracy: 0.8637 - val_loss: 0.3386 - val_categorical_accuracy: 0.8781 - 472ms/epoch - 24ms/step
Epoch 717/1500
20/20 - 0s - loss: 0.3340 - categorical_accuracy: 0.8776 - val_loss: 0.3668 - val_categorical_accuracy: 0.8602 - 482ms/epoch - 24ms/step
Epoch 718/1500
20/20 - 0s - loss: 0.3423 - categorical_accuracy: 0.8780 - val_loss: 0.4375 - val_categorical_accuracy: 0.8474 - 468ms/epoch - 23ms/step
Epoch 719/1500
20/20 - 0s - loss: 0.4019 - categorical_accuracy: 0.8609 - val_loss: 0.3390 - val_categorical_accuracy: 0.8804 - 465ms/epoch - 23ms/step
Epoch 720/1500
20/20 - 0s - loss: 0.3199 - categorical_accuracy: 0.8870 - val_loss: 0.3690 - val_categorical_accuracy: 0.8640 - 463ms/epoch - 23ms/step
Epoch 721/1500
20/20 - 0s - loss: 0.3391 - categorical_accuracy: 0.8747 - val_loss: 0.3584 - val_categorical_accuracy: 0.8713 - 467ms/epoch - 23ms/step
Epoch 722/1500
20/20 - 0s - loss: 0.3266 - categorical_accuracy: 0.8827 - val_loss: 0.3631 - val_categorical_accuracy: 0.8713 - 466ms/epoch - 23ms/step
Epoch 723/1500
20/20 - 0s - loss: 0.3396 - categorical_accuracy: 0.8754 - val_loss: 0.3668 - val_categorical_accuracy: 0.8691 - 458ms/epoch - 23ms/step
Epoch 724/1500
20/20 - 0s - loss: 0.3376 - categorical_accuracy: 0.8771 - val_loss: 0.3941 - val_categorical_accuracy: 0.8501 - 460ms/epoch - 23ms/step
Epoch 725/1500
20/20 - 0s - loss: 0.3542 - categorical_accuracy: 0.8684 - val_loss: 0.3601 - val_categorical_accuracy: 0.8662 - 465ms/epoch - 23ms/step
Epoch 726/1500
20/20 - 0s - loss: 0.3311 - categorical_accuracy: 0.8806 - val_loss: 0.3416 - val_categorical_accuracy: 0.8756 - 462ms/epoch - 23ms/step
Epoch 727/1500
20/20 - 0s - loss: 0.3524 - categorical_accuracy: 0.8714 - val_loss: 0.3538 - val_categorical_accuracy: 0.8710 - 474ms/epoch - 24ms/step
Epoch 728/1500
20/20 - 0s - loss: 0.3321 - categorical_accuracy: 0.8795 - val_loss: 0.3733 - val_categorical_accuracy: 0.8591 - 465ms/epoch - 23ms/step
Epoch 729/1500
20/20 - 0s - loss: 0.4313 - categorical_accuracy: 0.8442 - val_loss: 0.4961 - val_categorical_accuracy: 0.8266 - 470ms/epoch - 24ms/step
Epoch 730/1500
20/20 - 0s - loss: 0.3377 - categorical_accuracy: 0.8819 - val_loss: 0.3319 - val_categorical_accuracy: 0.8837 - 472ms/epoch - 24ms/step
Epoch 731/1500
20/20 - 0s - loss: 0.3189 - categorical_accuracy: 0.8868 - val_loss: 0.3600 - val_categorical_accuracy: 0.8706 - 470ms/epoch - 24ms/step
Epoch 732/1500
20/20 - 0s - loss: 0.3216 - categorical_accuracy: 0.8854 - val_loss: 0.3537 - val_categorical_accuracy: 0.8744 - 469ms/epoch - 23ms/step
Epoch 733/1500
20/20 - 0s - loss: 0.3252 - categorical_accuracy: 0.8843 - val_loss: 0.3654 - val_categorical_accuracy: 0.8651 - 470ms/epoch - 24ms/step
Epoch 734/1500
20/20 - 0s - loss: 0.3541 - categorical_accuracy: 0.8708 - val_loss: 0.3871 - val_categorical_accuracy: 0.8563 - 468ms/epoch - 23ms/step
Epoch 735/1500
20/20 - 0s - loss: 0.3375 - categorical_accuracy: 0.8768 - val_loss: 0.3742 - val_categorical_accuracy: 0.8594 - 471ms/epoch - 24ms/step
Epoch 736/1500
20/20 - 0s - loss: 0.3480 - categorical_accuracy: 0.8701 - val_loss: 0.3457 - val_categorical_accuracy: 0.8755 - 458ms/epoch - 23ms/step
Epoch 737/1500
20/20 - 0s - loss: 0.3265 - categorical_accuracy: 0.8818 - val_loss: 0.3594 - val_categorical_accuracy: 0.8685 - 467ms/epoch - 23ms/step
Epoch 738/1500
20/20 - 0s - loss: 0.3282 - categorical_accuracy: 0.8834 - val_loss: 0.3473 - val_categorical_accuracy: 0.8710 - 463ms/epoch - 23ms/step
Epoch 739/1500
20/20 - 0s - loss: 0.3165 - categorical_accuracy: 0.8879 - val_loss: 0.3691 - val_categorical_accuracy: 0.8625 - 472ms/epoch - 24ms/step
Epoch 740/1500
20/20 - 0s - loss: 0.3525 - categorical_accuracy: 0.8704 - val_loss: 0.3976 - val_categorical_accuracy: 0.8544 - 466ms/epoch - 23ms/step
Epoch 741/1500
20/20 - 0s - loss: 0.3346 - categorical_accuracy: 0.8788 - val_loss: 0.3529 - val_categorical_accuracy: 0.8722 - 458ms/epoch - 23ms/step
Epoch 742/1500
20/20 - 0s - loss: 0.3243 - categorical_accuracy: 0.8836 - val_loss: 0.3573 - val_categorical_accuracy: 0.8716 - 468ms/epoch - 23ms/step
Epoch 743/1500
20/20 - 0s - loss: 0.3195 - categorical_accuracy: 0.8874 - val_loss: 0.3458 - val_categorical_accuracy: 0.8816 - 466ms/epoch - 23ms/step
Epoch 744/1500
20/20 - 0s - loss: 0.3505 - categorical_accuracy: 0.8726 - val_loss: 0.3817 - val_categorical_accuracy: 0.8558 - 471ms/epoch - 24ms/step
Epoch 745/1500
20/20 - 0s - loss: 0.3290 - categorical_accuracy: 0.8791 - val_loss: 0.3336 - val_categorical_accuracy: 0.8787 - 484ms/epoch - 24ms/step
Epoch 746/1500
20/20 - 0s - loss: 0.3195 - categorical_accuracy: 0.8850 - val_loss: 0.3659 - val_categorical_accuracy: 0.8645 - 472ms/epoch - 24ms/step
Epoch 747/1500
20/20 - 0s - loss: 0.3316 - categorical_accuracy: 0.8801 - val_loss: 0.3729 - val_categorical_accuracy: 0.8667 - 486ms/epoch - 24ms/step
Epoch 748/1500
20/20 - 0s - loss: 0.4338 - categorical_accuracy: 0.8490 - val_loss: 0.3249 - val_categorical_accuracy: 0.8892 - 484ms/epoch - 24ms/step
Epoch 749/1500
20/20 - 0s - loss: 0.2988 - categorical_accuracy: 0.8983 - val_loss: 0.3188 - val_categorical_accuracy: 0.8897 - 474ms/epoch - 24ms/step
Epoch 750/1500
20/20 - 0s - loss: 0.3021 - categorical_accuracy: 0.8955 - val_loss: 0.3388 - val_categorical_accuracy: 0.8774 - 488ms/epoch - 24ms/step
Epoch 751/1500
20/20 - 0s - loss: 0.3284 - categorical_accuracy: 0.8806 - val_loss: 0.4116 - val_categorical_accuracy: 0.8423 - 477ms/epoch - 24ms/step
Epoch 752/1500
20/20 - 0s - loss: 0.3432 - categorical_accuracy: 0.8720 - val_loss: 0.3695 - val_categorical_accuracy: 0.8610 - 489ms/epoch - 24ms/step
Epoch 753/1500
20/20 - 0s - loss: 0.3296 - categorical_accuracy: 0.8794 - val_loss: 0.3340 - val_categorical_accuracy: 0.8811 - 495ms/epoch - 25ms/step
Epoch 754/1500
20/20 - 0s - loss: 0.3163 - categorical_accuracy: 0.8867 - val_loss: 0.3553 - val_categorical_accuracy: 0.8636 - 483ms/epoch - 24ms/step
Epoch 755/1500
20/20 - 0s - loss: 0.3242 - categorical_accuracy: 0.8801 - val_loss: 0.3348 - val_categorical_accuracy: 0.8808 - 475ms/epoch - 24ms/step
Epoch 756/1500
20/20 - 0s - loss: 0.3122 - categorical_accuracy: 0.8906 - val_loss: 0.3399 - val_categorical_accuracy: 0.8758 - 483ms/epoch - 24ms/step
Epoch 757/1500
20/20 - 0s - loss: 0.3408 - categorical_accuracy: 0.8751 - val_loss: 0.3762 - val_categorical_accuracy: 0.8609 - 467ms/epoch - 23ms/step
Epoch 758/1500
20/20 - 0s - loss: 0.3285 - categorical_accuracy: 0.8814 - val_loss: 0.3556 - val_categorical_accuracy: 0.8717 - 476ms/epoch - 24ms/step
Epoch 759/1500
20/20 - 0s - loss: 0.6163 - categorical_accuracy: 0.8210 - val_loss: 2.6012 - val_categorical_accuracy: 0.5511 - 476ms/epoch - 24ms/step
Epoch 760/1500
20/20 - 0s - loss: 0.7170 - categorical_accuracy: 0.8285 - val_loss: 0.3470 - val_categorical_accuracy: 0.8813 - 488ms/epoch - 24ms/step
Epoch 761/1500
20/20 - 0s - loss: 0.3170 - categorical_accuracy: 0.8934 - val_loss: 0.3346 - val_categorical_accuracy: 0.8860 - 476ms/epoch - 24ms/step
Epoch 762/1500
20/20 - 0s - loss: 0.3065 - categorical_accuracy: 0.8964 - val_loss: 0.3272 - val_categorical_accuracy: 0.8875 - 485ms/epoch - 24ms/step
Epoch 763/1500
20/20 - 0s - loss: 0.2997 - categorical_accuracy: 0.8984 - val_loss: 0.3204 - val_categorical_accuracy: 0.8894 - 492ms/epoch - 25ms/step
Epoch 764/1500
20/20 - 0s - loss: 0.2945 - categorical_accuracy: 0.9002 - val_loss: 0.3184 - val_categorical_accuracy: 0.8909 - 486ms/epoch - 24ms/step
Epoch 765/1500
20/20 - 0s - loss: 0.2974 - categorical_accuracy: 0.8981 - val_loss: 0.3334 - val_categorical_accuracy: 0.8793 - 484ms/epoch - 24ms/step
Epoch 766/1500
20/20 - 0s - loss: 0.3266 - categorical_accuracy: 0.8808 - val_loss: 0.3478 - val_categorical_accuracy: 0.8711 - 498ms/epoch - 25ms/step
Epoch 767/1500
20/20 - 0s - loss: 0.3107 - categorical_accuracy: 0.8890 - val_loss: 0.3313 - val_categorical_accuracy: 0.8802 - 496ms/epoch - 25ms/step
Epoch 768/1500
20/20 - 0s - loss: 0.3321 - categorical_accuracy: 0.8786 - val_loss: 0.3533 - val_categorical_accuracy: 0.8699 - 497ms/epoch - 25ms/step
Epoch 769/1500
20/20 - 1s - loss: 0.3283 - categorical_accuracy: 0.8826 - val_loss: 0.3226 - val_categorical_accuracy: 0.8856 - 506ms/epoch - 25ms/step
Epoch 770/1500
20/20 - 1s - loss: 0.3189 - categorical_accuracy: 0.8835 - val_loss: 0.3802 - val_categorical_accuracy: 0.8515 - 510ms/epoch - 26ms/step
Epoch 771/1500
20/20 - 0s - loss: 0.3257 - categorical_accuracy: 0.8815 - val_loss: 0.3329 - val_categorical_accuracy: 0.8815 - 498ms/epoch - 25ms/step
Epoch 772/1500
20/20 - 0s - loss: 0.3250 - categorical_accuracy: 0.8847 - val_loss: 0.3593 - val_categorical_accuracy: 0.8695 - 483ms/epoch - 24ms/step
Epoch 773/1500
20/20 - 0s - loss: 0.3315 - categorical_accuracy: 0.8797 - val_loss: 0.3512 - val_categorical_accuracy: 0.8736 - 483ms/epoch - 24ms/step
Epoch 774/1500
20/20 - 0s - loss: 0.3320 - categorical_accuracy: 0.8806 - val_loss: 0.3455 - val_categorical_accuracy: 0.8729 - 491ms/epoch - 25ms/step
Epoch 775/1500
20/20 - 0s - loss: 0.3258 - categorical_accuracy: 0.8790 - val_loss: 0.3604 - val_categorical_accuracy: 0.8599 - 489ms/epoch - 24ms/step
Epoch 776/1500
20/20 - 1s - loss: 0.3171 - categorical_accuracy: 0.8840 - val_loss: 0.3365 - val_categorical_accuracy: 0.8770 - 519ms/epoch - 26ms/step
Epoch 777/1500
20/20 - 1s - loss: 0.3157 - categorical_accuracy: 0.8861 - val_loss: 0.3552 - val_categorical_accuracy: 0.8700 - 504ms/epoch - 25ms/step
Epoch 778/1500
20/20 - 1s - loss: 0.3360 - categorical_accuracy: 0.8784 - val_loss: 0.3452 - val_categorical_accuracy: 0.8751 - 502ms/epoch - 25ms/step
Epoch 779/1500
20/20 - 1s - loss: 0.3090 - categorical_accuracy: 0.8904 - val_loss: 0.3363 - val_categorical_accuracy: 0.8785 - 501ms/epoch - 25ms/step
Epoch 780/1500
20/20 - 0s - loss: 0.3124 - categorical_accuracy: 0.8880 - val_loss: 0.3282 - val_categorical_accuracy: 0.8818 - 493ms/epoch - 25ms/step
Epoch 781/1500
20/20 - 0s - loss: 0.3183 - categorical_accuracy: 0.8839 - val_loss: 0.3631 - val_categorical_accuracy: 0.8666 - 499ms/epoch - 25ms/step
Epoch 782/1500
20/20 - 1s - loss: 0.3305 - categorical_accuracy: 0.8787 - val_loss: 0.3376 - val_categorical_accuracy: 0.8769 - 504ms/epoch - 25ms/step
Epoch 783/1500
20/20 - 1s - loss: 0.3086 - categorical_accuracy: 0.8916 - val_loss: 0.3459 - val_categorical_accuracy: 0.8732 - 502ms/epoch - 25ms/step
Epoch 784/1500
20/20 - 0s - loss: 0.3458 - categorical_accuracy: 0.8748 - val_loss: 0.5443 - val_categorical_accuracy: 0.7995 - 497ms/epoch - 25ms/step
Epoch 785/1500
20/20 - 0s - loss: 0.3982 - categorical_accuracy: 0.8707 - val_loss: 0.3087 - val_categorical_accuracy: 0.8936 - 478ms/epoch - 24ms/step
Epoch 786/1500
20/20 - 0s - loss: 0.2852 - categorical_accuracy: 0.9025 - val_loss: 0.3124 - val_categorical_accuracy: 0.8892 - 466ms/epoch - 23ms/step
Epoch 787/1500
20/20 - 0s - loss: 0.3105 - categorical_accuracy: 0.8872 - val_loss: 0.3518 - val_categorical_accuracy: 0.8655 - 462ms/epoch - 23ms/step
Epoch 788/1500
20/20 - 0s - loss: 0.3122 - categorical_accuracy: 0.8860 - val_loss: 0.3317 - val_categorical_accuracy: 0.8774 - 462ms/epoch - 23ms/step
Epoch 789/1500
20/20 - 0s - loss: 0.3228 - categorical_accuracy: 0.8800 - val_loss: 0.3615 - val_categorical_accuracy: 0.8598 - 472ms/epoch - 24ms/step
Epoch 790/1500
20/20 - 0s - loss: 0.3059 - categorical_accuracy: 0.8913 - val_loss: 0.3215 - val_categorical_accuracy: 0.8839 - 468ms/epoch - 23ms/step
Epoch 791/1500
20/20 - 0s - loss: 0.3036 - categorical_accuracy: 0.8939 - val_loss: 0.3391 - val_categorical_accuracy: 0.8805 - 456ms/epoch - 23ms/step
Epoch 792/1500
20/20 - 0s - loss: 0.3524 - categorical_accuracy: 0.8694 - val_loss: 0.4014 - val_categorical_accuracy: 0.8501 - 456ms/epoch - 23ms/step
Epoch 793/1500
20/20 - 0s - loss: 0.3138 - categorical_accuracy: 0.8875 - val_loss: 0.3168 - val_categorical_accuracy: 0.8885 - 456ms/epoch - 23ms/step
Epoch 794/1500
20/20 - 0s - loss: 0.2952 - categorical_accuracy: 0.8970 - val_loss: 0.3470 - val_categorical_accuracy: 0.8690 - 446ms/epoch - 22ms/step
Epoch 795/1500
20/20 - 0s - loss: 0.3105 - categorical_accuracy: 0.8886 - val_loss: 0.3165 - val_categorical_accuracy: 0.8884 - 452ms/epoch - 23ms/step
Epoch 796/1500
20/20 - 0s - loss: 0.3143 - categorical_accuracy: 0.8860 - val_loss: 0.3775 - val_categorical_accuracy: 0.8595 - 452ms/epoch - 23ms/step
Epoch 797/1500
20/20 - 0s - loss: 0.3303 - categorical_accuracy: 0.8774 - val_loss: 0.3441 - val_categorical_accuracy: 0.8737 - 459ms/epoch - 23ms/step
Epoch 798/1500
20/20 - 0s - loss: 0.3190 - categorical_accuracy: 0.8835 - val_loss: 0.3554 - val_categorical_accuracy: 0.8694 - 468ms/epoch - 23ms/step
Epoch 799/1500
20/20 - 0s - loss: 0.3033 - categorical_accuracy: 0.8923 - val_loss: 0.3150 - val_categorical_accuracy: 0.8897 - 469ms/epoch - 23ms/step
Epoch 800/1500
20/20 - 0s - loss: 0.2854 - categorical_accuracy: 0.9022 - val_loss: 0.3118 - val_categorical_accuracy: 0.8893 - 463ms/epoch - 23ms/step
Epoch 801/1500
20/20 - 0s - loss: 0.4768 - categorical_accuracy: 0.8418 - val_loss: 0.3729 - val_categorical_accuracy: 0.8691 - 466ms/epoch - 23ms/step
Epoch 802/1500
20/20 - 0s - loss: 0.2959 - categorical_accuracy: 0.8977 - val_loss: 0.3123 - val_categorical_accuracy: 0.8902 - 484ms/epoch - 24ms/step
Epoch 803/1500
20/20 - 0s - loss: 0.2994 - categorical_accuracy: 0.8942 - val_loss: 0.3324 - val_categorical_accuracy: 0.8795 - 476ms/epoch - 24ms/step
Epoch 804/1500
20/20 - 0s - loss: 0.3150 - categorical_accuracy: 0.8860 - val_loss: 0.3299 - val_categorical_accuracy: 0.8797 - 485ms/epoch - 24ms/step
Epoch 805/1500
20/20 - 1s - loss: 0.2964 - categorical_accuracy: 0.8956 - val_loss: 0.3084 - val_categorical_accuracy: 0.8918 - 507ms/epoch - 25ms/step
Epoch 806/1500
20/20 - 0s - loss: 0.2890 - categorical_accuracy: 0.8994 - val_loss: 0.3619 - val_categorical_accuracy: 0.8635 - 486ms/epoch - 24ms/step
Epoch 807/1500
20/20 - 0s - loss: 0.3345 - categorical_accuracy: 0.8762 - val_loss: 0.3266 - val_categorical_accuracy: 0.8820 - 474ms/epoch - 24ms/step
Epoch 808/1500
20/20 - 0s - loss: 0.3043 - categorical_accuracy: 0.8932 - val_loss: 0.3671 - val_categorical_accuracy: 0.8717 - 487ms/epoch - 24ms/step
Epoch 809/1500
20/20 - 0s - loss: 0.4105 - categorical_accuracy: 0.8664 - val_loss: 0.3030 - val_categorical_accuracy: 0.8966 - 474ms/epoch - 24ms/step
Epoch 810/1500
20/20 - 0s - loss: 0.2924 - categorical_accuracy: 0.8978 - val_loss: 0.3366 - val_categorical_accuracy: 0.8806 - 476ms/epoch - 24ms/step
Epoch 811/1500
20/20 - 0s - loss: 0.3144 - categorical_accuracy: 0.8851 - val_loss: 0.3347 - val_categorical_accuracy: 0.8783 - 474ms/epoch - 24ms/step
Epoch 812/1500
20/20 - 0s - loss: 0.3139 - categorical_accuracy: 0.8839 - val_loss: 0.3550 - val_categorical_accuracy: 0.8676 - 480ms/epoch - 24ms/step
Epoch 813/1500
20/20 - 0s - loss: 0.3091 - categorical_accuracy: 0.8870 - val_loss: 0.3200 - val_categorical_accuracy: 0.8865 - 468ms/epoch - 23ms/step
Epoch 814/1500
20/20 - 0s - loss: 0.3002 - categorical_accuracy: 0.8915 - val_loss: 0.3236 - val_categorical_accuracy: 0.8852 - 470ms/epoch - 24ms/step
Epoch 815/1500
20/20 - 0s - loss: 0.3131 - categorical_accuracy: 0.8862 - val_loss: 0.3546 - val_categorical_accuracy: 0.8693 - 484ms/epoch - 24ms/step
Epoch 816/1500
20/20 - 0s - loss: 0.3170 - categorical_accuracy: 0.8852 - val_loss: 0.3600 - val_categorical_accuracy: 0.8654 - 474ms/epoch - 24ms/step
Epoch 817/1500
20/20 - 0s - loss: 0.3184 - categorical_accuracy: 0.8842 - val_loss: 0.3175 - val_categorical_accuracy: 0.8861 - 471ms/epoch - 24ms/step
Epoch 818/1500
20/20 - 0s - loss: 0.3177 - categorical_accuracy: 0.8825 - val_loss: 0.3199 - val_categorical_accuracy: 0.8846 - 490ms/epoch - 25ms/step
Epoch 819/1500
20/20 - 0s - loss: 0.2873 - categorical_accuracy: 0.8996 - val_loss: 0.3129 - val_categorical_accuracy: 0.8893 - 474ms/epoch - 24ms/step
Epoch 820/1500
20/20 - 0s - loss: 0.3226 - categorical_accuracy: 0.8820 - val_loss: 0.3496 - val_categorical_accuracy: 0.8723 - 482ms/epoch - 24ms/step
Epoch 821/1500
20/20 - 0s - loss: 0.2983 - categorical_accuracy: 0.8956 - val_loss: 0.3236 - val_categorical_accuracy: 0.8822 - 481ms/epoch - 24ms/step
Epoch 822/1500
20/20 - 0s - loss: 0.3085 - categorical_accuracy: 0.8899 - val_loss: 0.3261 - val_categorical_accuracy: 0.8826 - 489ms/epoch - 24ms/step
Epoch 823/1500
20/20 - 1s - loss: 0.2947 - categorical_accuracy: 0.8980 - val_loss: 0.3239 - val_categorical_accuracy: 0.8842 - 500ms/epoch - 25ms/step
Epoch 824/1500
20/20 - 1s - loss: 0.3168 - categorical_accuracy: 0.8829 - val_loss: 0.3555 - val_categorical_accuracy: 0.8695 - 500ms/epoch - 25ms/step
Epoch 825/1500
20/20 - 0s - loss: 0.3263 - categorical_accuracy: 0.8799 - val_loss: 0.5502 - val_categorical_accuracy: 0.8027 - 492ms/epoch - 25ms/step
Epoch 826/1500
20/20 - 1s - loss: 0.4120 - categorical_accuracy: 0.8609 - val_loss: 0.3009 - val_categorical_accuracy: 0.8972 - 500ms/epoch - 25ms/step
Epoch 827/1500
20/20 - 1s - loss: 0.2751 - categorical_accuracy: 0.9066 - val_loss: 0.3022 - val_categorical_accuracy: 0.8944 - 504ms/epoch - 25ms/step
Epoch 828/1500
20/20 - 0s - loss: 0.2957 - categorical_accuracy: 0.8942 - val_loss: 0.3580 - val_categorical_accuracy: 0.8716 - 482ms/epoch - 24ms/step
Epoch 829/1500
20/20 - 0s - loss: 0.3022 - categorical_accuracy: 0.8915 - val_loss: 0.3326 - val_categorical_accuracy: 0.8779 - 495ms/epoch - 25ms/step
Epoch 830/1500
20/20 - 0s - loss: 0.3126 - categorical_accuracy: 0.8846 - val_loss: 0.3460 - val_categorical_accuracy: 0.8740 - 492ms/epoch - 25ms/step
Epoch 831/1500
20/20 - 1s - loss: 0.3146 - categorical_accuracy: 0.8847 - val_loss: 0.3408 - val_categorical_accuracy: 0.8769 - 503ms/epoch - 25ms/step
Epoch 832/1500
20/20 - 0s - loss: 0.3062 - categorical_accuracy: 0.8908 - val_loss: 0.3021 - val_categorical_accuracy: 0.8945 - 498ms/epoch - 25ms/step
Epoch 833/1500
20/20 - 0s - loss: 0.2867 - categorical_accuracy: 0.9011 - val_loss: 0.3212 - val_categorical_accuracy: 0.8885 - 486ms/epoch - 24ms/step
Epoch 834/1500
20/20 - 0s - loss: 0.2986 - categorical_accuracy: 0.8945 - val_loss: 0.3311 - val_categorical_accuracy: 0.8812 - 492ms/epoch - 25ms/step
Epoch 835/1500
20/20 - 0s - loss: 0.2938 - categorical_accuracy: 0.8954 - val_loss: 0.3522 - val_categorical_accuracy: 0.8697 - 486ms/epoch - 24ms/step
Epoch 836/1500
20/20 - 0s - loss: 0.3323 - categorical_accuracy: 0.8732 - val_loss: 0.3410 - val_categorical_accuracy: 0.8752 - 488ms/epoch - 24ms/step
Epoch 837/1500
20/20 - 0s - loss: 0.2910 - categorical_accuracy: 0.8955 - val_loss: 0.3168 - val_categorical_accuracy: 0.8877 - 488ms/epoch - 24ms/step
Epoch 838/1500
20/20 - 0s - loss: 0.4184 - categorical_accuracy: 0.8630 - val_loss: 0.5073 - val_categorical_accuracy: 0.8237 - 495ms/epoch - 25ms/step
Epoch 839/1500
20/20 - 0s - loss: 0.3021 - categorical_accuracy: 0.8976 - val_loss: 0.2939 - val_categorical_accuracy: 0.8997 - 476ms/epoch - 24ms/step
Epoch 840/1500
20/20 - 0s - loss: 0.2810 - categorical_accuracy: 0.9027 - val_loss: 0.3027 - val_categorical_accuracy: 0.8924 - 488ms/epoch - 24ms/step
Epoch 841/1500
20/20 - 0s - loss: 0.2957 - categorical_accuracy: 0.8931 - val_loss: 0.3301 - val_categorical_accuracy: 0.8767 - 490ms/epoch - 25ms/step
Epoch 842/1500
20/20 - 0s - loss: 0.3122 - categorical_accuracy: 0.8842 - val_loss: 0.3323 - val_categorical_accuracy: 0.8764 - 480ms/epoch - 24ms/step
Epoch 843/1500
20/20 - 0s - loss: 0.3231 - categorical_accuracy: 0.8814 - val_loss: 0.3265 - val_categorical_accuracy: 0.8814 - 458ms/epoch - 23ms/step
Epoch 844/1500
20/20 - 0s - loss: 0.2994 - categorical_accuracy: 0.8944 - val_loss: 0.3301 - val_categorical_accuracy: 0.8817 - 464ms/epoch - 23ms/step
Epoch 845/1500
20/20 - 0s - loss: 0.2878 - categorical_accuracy: 0.8996 - val_loss: 0.3194 - val_categorical_accuracy: 0.8840 - 456ms/epoch - 23ms/step
Epoch 846/1500
20/20 - 0s - loss: 0.2965 - categorical_accuracy: 0.8927 - val_loss: 0.3422 - val_categorical_accuracy: 0.8685 - 472ms/epoch - 24ms/step
Epoch 847/1500
20/20 - 0s - loss: 0.3140 - categorical_accuracy: 0.8819 - val_loss: 0.3287 - val_categorical_accuracy: 0.8762 - 465ms/epoch - 23ms/step
Epoch 848/1500
20/20 - 0s - loss: 0.2862 - categorical_accuracy: 0.8991 - val_loss: 0.3059 - val_categorical_accuracy: 0.8909 - 467ms/epoch - 23ms/step
Epoch 849/1500
20/20 - 0s - loss: 0.2915 - categorical_accuracy: 0.8961 - val_loss: 0.3462 - val_categorical_accuracy: 0.8706 - 479ms/epoch - 24ms/step
Epoch 850/1500
20/20 - 0s - loss: 0.4289 - categorical_accuracy: 0.8529 - val_loss: 0.3613 - val_categorical_accuracy: 0.8732 - 462ms/epoch - 23ms/step
Epoch 851/1500
20/20 - 0s - loss: 0.2729 - categorical_accuracy: 0.9081 - val_loss: 0.2978 - val_categorical_accuracy: 0.8955 - 465ms/epoch - 23ms/step
Epoch 852/1500
20/20 - 0s - loss: 0.2777 - categorical_accuracy: 0.9042 - val_loss: 0.3170 - val_categorical_accuracy: 0.8847 - 462ms/epoch - 23ms/step
Epoch 853/1500
20/20 - 0s - loss: 0.3043 - categorical_accuracy: 0.8890 - val_loss: 0.3545 - val_categorical_accuracy: 0.8665 - 471ms/epoch - 24ms/step
Epoch 854/1500
20/20 - 0s - loss: 0.3111 - categorical_accuracy: 0.8865 - val_loss: 0.3204 - val_categorical_accuracy: 0.8827 - 459ms/epoch - 23ms/step
Epoch 855/1500
20/20 - 0s - loss: 0.2964 - categorical_accuracy: 0.8947 - val_loss: 0.3119 - val_categorical_accuracy: 0.8887 - 475ms/epoch - 24ms/step
Epoch 856/1500
20/20 - 0s - loss: 0.2853 - categorical_accuracy: 0.8992 - val_loss: 0.3105 - val_categorical_accuracy: 0.8898 - 469ms/epoch - 23ms/step
Epoch 857/1500
20/20 - 0s - loss: 0.3053 - categorical_accuracy: 0.8881 - val_loss: 0.3582 - val_categorical_accuracy: 0.8676 - 480ms/epoch - 24ms/step
Epoch 858/1500
20/20 - 0s - loss: 0.3031 - categorical_accuracy: 0.8896 - val_loss: 0.3263 - val_categorical_accuracy: 0.8836 - 469ms/epoch - 23ms/step
Epoch 859/1500
20/20 - 0s - loss: 0.2780 - categorical_accuracy: 0.9030 - val_loss: 0.2993 - val_categorical_accuracy: 0.8949 - 484ms/epoch - 24ms/step
Epoch 860/1500
20/20 - 0s - loss: 0.2830 - categorical_accuracy: 0.8993 - val_loss: 0.3383 - val_categorical_accuracy: 0.8768 - 479ms/epoch - 24ms/step
Epoch 861/1500
20/20 - 0s - loss: 0.3241 - categorical_accuracy: 0.8784 - val_loss: 0.3999 - val_categorical_accuracy: 0.8512 - 485ms/epoch - 24ms/step
Epoch 862/1500
20/20 - 1s - loss: 0.3190 - categorical_accuracy: 0.8854 - val_loss: 0.3028 - val_categorical_accuracy: 0.8925 - 509ms/epoch - 25ms/step
Epoch 863/1500
20/20 - 0s - loss: 0.2837 - categorical_accuracy: 0.8999 - val_loss: 0.2966 - val_categorical_accuracy: 0.8960 - 494ms/epoch - 25ms/step
Epoch 864/1500
20/20 - 0s - loss: 0.2759 - categorical_accuracy: 0.9035 - val_loss: 0.3327 - val_categorical_accuracy: 0.8807 - 478ms/epoch - 24ms/step
Epoch 865/1500
20/20 - 0s - loss: 0.3048 - categorical_accuracy: 0.8901 - val_loss: 0.3173 - val_categorical_accuracy: 0.8870 - 476ms/epoch - 24ms/step
Epoch 866/1500
20/20 - 0s - loss: 0.2704 - categorical_accuracy: 0.9067 - val_loss: 0.3025 - val_categorical_accuracy: 0.8935 - 486ms/epoch - 24ms/step
Epoch 867/1500
20/20 - 0s - loss: 0.2814 - categorical_accuracy: 0.9010 - val_loss: 0.3185 - val_categorical_accuracy: 0.8871 - 467ms/epoch - 23ms/step
Epoch 868/1500
20/20 - 0s - loss: 0.2956 - categorical_accuracy: 0.8946 - val_loss: 0.3042 - val_categorical_accuracy: 0.8937 - 473ms/epoch - 24ms/step
Epoch 869/1500
20/20 - 0s - loss: 0.2798 - categorical_accuracy: 0.9018 - val_loss: 0.3348 - val_categorical_accuracy: 0.8765 - 467ms/epoch - 23ms/step
Epoch 870/1500
20/20 - 0s - loss: 0.3934 - categorical_accuracy: 0.8530 - val_loss: 0.5505 - val_categorical_accuracy: 0.8172 - 479ms/epoch - 24ms/step
Epoch 871/1500
20/20 - 0s - loss: 0.3792 - categorical_accuracy: 0.8744 - val_loss: 0.2887 - val_categorical_accuracy: 0.9011 - 460ms/epoch - 23ms/step
Epoch 872/1500
20/20 - 0s - loss: 0.2584 - categorical_accuracy: 0.9145 - val_loss: 0.2826 - val_categorical_accuracy: 0.9037 - 467ms/epoch - 23ms/step
Epoch 873/1500
20/20 - 0s - loss: 0.2587 - categorical_accuracy: 0.9124 - val_loss: 0.2960 - val_categorical_accuracy: 0.8948 - 471ms/epoch - 24ms/step
Epoch 874/1500
20/20 - 0s - loss: 0.3098 - categorical_accuracy: 0.8844 - val_loss: 0.3199 - val_categorical_accuracy: 0.8797 - 458ms/epoch - 23ms/step
Epoch 875/1500
20/20 - 0s - loss: 0.2854 - categorical_accuracy: 0.8977 - val_loss: 0.3132 - val_categorical_accuracy: 0.8848 - 465ms/epoch - 23ms/step
Epoch 876/1500
20/20 - 0s - loss: 0.2847 - categorical_accuracy: 0.8976 - val_loss: 0.3069 - val_categorical_accuracy: 0.8888 - 468ms/epoch - 23ms/step
Epoch 877/1500
20/20 - 0s - loss: 0.2864 - categorical_accuracy: 0.8963 - val_loss: 0.3336 - val_categorical_accuracy: 0.8748 - 476ms/epoch - 24ms/step
Epoch 878/1500
20/20 - 0s - loss: 0.3123 - categorical_accuracy: 0.8838 - val_loss: 0.3858 - val_categorical_accuracy: 0.8564 - 467ms/epoch - 23ms/step
Epoch 879/1500
20/20 - 0s - loss: 0.3012 - categorical_accuracy: 0.8914 - val_loss: 0.3023 - val_categorical_accuracy: 0.8931 - 473ms/epoch - 24ms/step
Epoch 880/1500
20/20 - 0s - loss: 0.2615 - categorical_accuracy: 0.9108 - val_loss: 0.2960 - val_categorical_accuracy: 0.8957 - 473ms/epoch - 24ms/step
Epoch 881/1500
20/20 - 0s - loss: 0.2961 - categorical_accuracy: 0.8924 - val_loss: 0.3180 - val_categorical_accuracy: 0.8868 - 482ms/epoch - 24ms/step
Epoch 882/1500
20/20 - 0s - loss: 0.2752 - categorical_accuracy: 0.9029 - val_loss: 0.2956 - val_categorical_accuracy: 0.8952 - 471ms/epoch - 24ms/step
Epoch 883/1500
20/20 - 0s - loss: 0.2975 - categorical_accuracy: 0.8925 - val_loss: 0.3296 - val_categorical_accuracy: 0.8773 - 464ms/epoch - 23ms/step
Epoch 884/1500
20/20 - 0s - loss: 0.3040 - categorical_accuracy: 0.8865 - val_loss: 0.3182 - val_categorical_accuracy: 0.8825 - 474ms/epoch - 24ms/step
Epoch 885/1500
20/20 - 0s - loss: 0.2812 - categorical_accuracy: 0.8987 - val_loss: 0.3105 - val_categorical_accuracy: 0.8876 - 467ms/epoch - 23ms/step
Epoch 886/1500
20/20 - 0s - loss: 0.2876 - categorical_accuracy: 0.8955 - val_loss: 0.3187 - val_categorical_accuracy: 0.8828 - 475ms/epoch - 24ms/step
Epoch 887/1500
20/20 - 0s - loss: 0.2855 - categorical_accuracy: 0.8977 - val_loss: 0.3001 - val_categorical_accuracy: 0.8934 - 470ms/epoch - 24ms/step
Epoch 888/1500
20/20 - 0s - loss: 0.2913 - categorical_accuracy: 0.8985 - val_loss: 0.3448 - val_categorical_accuracy: 0.8775 - 473ms/epoch - 24ms/step
Epoch 889/1500
20/20 - 0s - loss: 0.3997 - categorical_accuracy: 0.8717 - val_loss: 0.2823 - val_categorical_accuracy: 0.9035 - 480ms/epoch - 24ms/step
Epoch 890/1500
20/20 - 0s - loss: 0.2580 - categorical_accuracy: 0.9132 - val_loss: 0.3088 - val_categorical_accuracy: 0.8885 - 470ms/epoch - 24ms/step
Epoch 891/1500
20/20 - 0s - loss: 0.3000 - categorical_accuracy: 0.8883 - val_loss: 0.3019 - val_categorical_accuracy: 0.8920 - 466ms/epoch - 23ms/step
Epoch 892/1500
20/20 - 0s - loss: 0.2683 - categorical_accuracy: 0.9059 - val_loss: 0.2967 - val_categorical_accuracy: 0.8948 - 479ms/epoch - 24ms/step
Epoch 893/1500
20/20 - 0s - loss: 0.2876 - categorical_accuracy: 0.8948 - val_loss: 0.3309 - val_categorical_accuracy: 0.8821 - 473ms/epoch - 24ms/step
Epoch 894/1500
20/20 - 0s - loss: 0.2896 - categorical_accuracy: 0.8958 - val_loss: 0.3131 - val_categorical_accuracy: 0.8869 - 464ms/epoch - 23ms/step
Epoch 895/1500
20/20 - 0s - loss: 0.2834 - categorical_accuracy: 0.8988 - val_loss: 0.3200 - val_categorical_accuracy: 0.8837 - 478ms/epoch - 24ms/step
Epoch 896/1500
20/20 - 0s - loss: 0.2982 - categorical_accuracy: 0.8920 - val_loss: 0.3439 - val_categorical_accuracy: 0.8708 - 469ms/epoch - 23ms/step
Epoch 897/1500
20/20 - 0s - loss: 0.2845 - categorical_accuracy: 0.8980 - val_loss: 0.3292 - val_categorical_accuracy: 0.8772 - 480ms/epoch - 24ms/step
Epoch 898/1500
20/20 - 0s - loss: 0.2870 - categorical_accuracy: 0.8955 - val_loss: 0.3286 - val_categorical_accuracy: 0.8768 - 474ms/epoch - 24ms/step
Epoch 899/1500
20/20 - 0s - loss: 0.2809 - categorical_accuracy: 0.8990 - val_loss: 0.3108 - val_categorical_accuracy: 0.8890 - 472ms/epoch - 24ms/step
Epoch 900/1500
20/20 - 0s - loss: 0.2812 - categorical_accuracy: 0.8994 - val_loss: 0.3332 - val_categorical_accuracy: 0.8751 - 471ms/epoch - 24ms/step
Epoch 901/1500
20/20 - 0s - loss: 0.2821 - categorical_accuracy: 0.9014 - val_loss: 0.2890 - val_categorical_accuracy: 0.9001 - 482ms/epoch - 24ms/step
Epoch 902/1500
20/20 - 0s - loss: 0.2781 - categorical_accuracy: 0.9021 - val_loss: 0.3434 - val_categorical_accuracy: 0.8727 - 473ms/epoch - 24ms/step
Epoch 903/1500
20/20 - 0s - loss: 0.3245 - categorical_accuracy: 0.8827 - val_loss: 0.3494 - val_categorical_accuracy: 0.8793 - 471ms/epoch - 24ms/step
Epoch 904/1500
20/20 - 0s - loss: 0.2784 - categorical_accuracy: 0.9041 - val_loss: 0.2929 - val_categorical_accuracy: 0.8952 - 488ms/epoch - 24ms/step
Epoch 905/1500
20/20 - 0s - loss: 0.2971 - categorical_accuracy: 0.8925 - val_loss: 0.3238 - val_categorical_accuracy: 0.8814 - 490ms/epoch - 25ms/step
Epoch 906/1500
20/20 - 0s - loss: 0.2894 - categorical_accuracy: 0.8973 - val_loss: 0.2946 - val_categorical_accuracy: 0.8947 - 473ms/epoch - 24ms/step
Epoch 907/1500
20/20 - 0s - loss: 0.2705 - categorical_accuracy: 0.9066 - val_loss: 0.2889 - val_categorical_accuracy: 0.8983 - 474ms/epoch - 24ms/step
Epoch 908/1500
20/20 - 0s - loss: 0.2810 - categorical_accuracy: 0.9002 - val_loss: 0.3351 - val_categorical_accuracy: 0.8796 - 474ms/epoch - 24ms/step
Epoch 909/1500
20/20 - 0s - loss: 0.2942 - categorical_accuracy: 0.8910 - val_loss: 0.3239 - val_categorical_accuracy: 0.8814 - 474ms/epoch - 24ms/step
Epoch 910/1500
20/20 - 0s - loss: 0.2707 - categorical_accuracy: 0.9041 - val_loss: 0.2973 - val_categorical_accuracy: 0.8959 - 478ms/epoch - 24ms/step
Epoch 911/1500
20/20 - 0s - loss: 0.2664 - categorical_accuracy: 0.9073 - val_loss: 0.3032 - val_categorical_accuracy: 0.8917 - 469ms/epoch - 23ms/step
Epoch 912/1500
20/20 - 0s - loss: 0.2953 - categorical_accuracy: 0.8893 - val_loss: 0.3084 - val_categorical_accuracy: 0.8891 - 478ms/epoch - 24ms/step
Epoch 913/1500
20/20 - 0s - loss: 0.3569 - categorical_accuracy: 0.8763 - val_loss: 1.2256 - val_categorical_accuracy: 0.7781 - 464ms/epoch - 23ms/step
Epoch 914/1500
20/20 - 0s - loss: 1.2081 - categorical_accuracy: 0.7735 - val_loss: 0.3301 - val_categorical_accuracy: 0.8894 - 494ms/epoch - 25ms/step
Epoch 915/1500
20/20 - 1s - loss: 0.2913 - categorical_accuracy: 0.9045 - val_loss: 0.3070 - val_categorical_accuracy: 0.8971 - 503ms/epoch - 25ms/step
Epoch 916/1500
20/20 - 1s - loss: 0.2747 - categorical_accuracy: 0.9103 - val_loss: 0.2942 - val_categorical_accuracy: 0.9010 - 501ms/epoch - 25ms/step
Epoch 917/1500
20/20 - 0s - loss: 0.2646 - categorical_accuracy: 0.9132 - val_loss: 0.2887 - val_categorical_accuracy: 0.9015 - 495ms/epoch - 25ms/step
Epoch 918/1500
20/20 - 1s - loss: 0.2578 - categorical_accuracy: 0.9153 - val_loss: 0.2827 - val_categorical_accuracy: 0.9036 - 501ms/epoch - 25ms/step
Epoch 919/1500
20/20 - 0s - loss: 0.2538 - categorical_accuracy: 0.9162 - val_loss: 0.2812 - val_categorical_accuracy: 0.9034 - 489ms/epoch - 24ms/step
Epoch 920/1500
20/20 - 0s - loss: 0.2550 - categorical_accuracy: 0.9143 - val_loss: 0.2785 - val_categorical_accuracy: 0.9044 - 489ms/epoch - 24ms/step
Epoch 921/1500
20/20 - 1s - loss: 0.2626 - categorical_accuracy: 0.9097 - val_loss: 0.2924 - val_categorical_accuracy: 0.8986 - 505ms/epoch - 25ms/step
Epoch 922/1500
20/20 - 0s - loss: 0.2771 - categorical_accuracy: 0.9017 - val_loss: 0.2836 - val_categorical_accuracy: 0.9018 - 484ms/epoch - 24ms/step
Epoch 923/1500
20/20 - 0s - loss: 0.2771 - categorical_accuracy: 0.9024 - val_loss: 0.3471 - val_categorical_accuracy: 0.8714 - 495ms/epoch - 25ms/step
Epoch 924/1500
20/20 - 0s - loss: 0.2929 - categorical_accuracy: 0.8952 - val_loss: 0.2903 - val_categorical_accuracy: 0.8988 - 498ms/epoch - 25ms/step
Epoch 925/1500
20/20 - 0s - loss: 0.2817 - categorical_accuracy: 0.8979 - val_loss: 0.3182 - val_categorical_accuracy: 0.8838 - 496ms/epoch - 25ms/step
Epoch 926/1500
20/20 - 0s - loss: 0.2734 - categorical_accuracy: 0.9022 - val_loss: 0.2957 - val_categorical_accuracy: 0.8958 - 499ms/epoch - 25ms/step
Epoch 927/1500
20/20 - 1s - loss: 0.2689 - categorical_accuracy: 0.9058 - val_loss: 0.3008 - val_categorical_accuracy: 0.8940 - 510ms/epoch - 26ms/step
Epoch 928/1500
20/20 - 0s - loss: 0.2775 - categorical_accuracy: 0.9018 - val_loss: 0.3132 - val_categorical_accuracy: 0.8871 - 496ms/epoch - 25ms/step
Epoch 929/1500
20/20 - 1s - loss: 0.2834 - categorical_accuracy: 0.8985 - val_loss: 0.2882 - val_categorical_accuracy: 0.8978 - 505ms/epoch - 25ms/step
Epoch 930/1500
20/20 - 0s - loss: 0.2659 - categorical_accuracy: 0.9075 - val_loss: 0.2989 - val_categorical_accuracy: 0.8944 - 494ms/epoch - 25ms/step
Epoch 931/1500
20/20 - 1s - loss: 0.2904 - categorical_accuracy: 0.8928 - val_loss: 0.3173 - val_categorical_accuracy: 0.8802 - 500ms/epoch - 25ms/step
Epoch 932/1500
20/20 - 0s - loss: 0.2716 - categorical_accuracy: 0.9029 - val_loss: 0.2787 - val_categorical_accuracy: 0.9022 - 479ms/epoch - 24ms/step
Epoch 933/1500
20/20 - 0s - loss: 0.2674 - categorical_accuracy: 0.9056 - val_loss: 0.3004 - val_categorical_accuracy: 0.8950 - 479ms/epoch - 24ms/step
Epoch 934/1500
20/20 - 0s - loss: 0.3157 - categorical_accuracy: 0.8860 - val_loss: 0.4285 - val_categorical_accuracy: 0.8423 - 470ms/epoch - 24ms/step
Epoch 935/1500
20/20 - 0s - loss: 0.3726 - categorical_accuracy: 0.8827 - val_loss: 0.2721 - val_categorical_accuracy: 0.9070 - 471ms/epoch - 24ms/step
Epoch 936/1500
20/20 - 0s - loss: 0.2492 - categorical_accuracy: 0.9159 - val_loss: 0.2914 - val_categorical_accuracy: 0.8958 - 473ms/epoch - 24ms/step
Epoch 937/1500
20/20 - 0s - loss: 0.2661 - categorical_accuracy: 0.9068 - val_loss: 0.3079 - val_categorical_accuracy: 0.8881 - 492ms/epoch - 25ms/step
Epoch 938/1500
20/20 - 0s - loss: 0.2849 - categorical_accuracy: 0.8968 - val_loss: 0.3108 - val_categorical_accuracy: 0.8865 - 493ms/epoch - 25ms/step
Epoch 939/1500
20/20 - 0s - loss: 0.2800 - categorical_accuracy: 0.8985 - val_loss: 0.3773 - val_categorical_accuracy: 0.8549 - 499ms/epoch - 25ms/step
Epoch 940/1500
20/20 - 0s - loss: 0.2971 - categorical_accuracy: 0.8894 - val_loss: 0.2874 - val_categorical_accuracy: 0.8979 - 488ms/epoch - 24ms/step
Epoch 941/1500
20/20 - 0s - loss: 0.2558 - categorical_accuracy: 0.9112 - val_loss: 0.2843 - val_categorical_accuracy: 0.8992 - 484ms/epoch - 24ms/step
Epoch 942/1500
20/20 - 0s - loss: 0.2845 - categorical_accuracy: 0.8976 - val_loss: 0.3036 - val_categorical_accuracy: 0.8907 - 482ms/epoch - 24ms/step
Epoch 943/1500
20/20 - 0s - loss: 0.2713 - categorical_accuracy: 0.9033 - val_loss: 0.2753 - val_categorical_accuracy: 0.9038 - 486ms/epoch - 24ms/step
Epoch 944/1500
20/20 - 0s - loss: 0.2760 - categorical_accuracy: 0.8999 - val_loss: 0.3233 - val_categorical_accuracy: 0.8816 - 481ms/epoch - 24ms/step
Epoch 945/1500
20/20 - 0s - loss: 0.2889 - categorical_accuracy: 0.8944 - val_loss: 0.2986 - val_categorical_accuracy: 0.8929 - 481ms/epoch - 24ms/step
Epoch 946/1500
20/20 - 1s - loss: 0.2533 - categorical_accuracy: 0.9121 - val_loss: 0.2745 - val_categorical_accuracy: 0.9049 - 500ms/epoch - 25ms/step
Epoch 947/1500
20/20 - 0s - loss: 0.2425 - categorical_accuracy: 0.9178 - val_loss: 0.2789 - val_categorical_accuracy: 0.9024 - 491ms/epoch - 25ms/step
Epoch 948/1500
20/20 - 0s - loss: 0.2890 - categorical_accuracy: 0.8934 - val_loss: 0.3055 - val_categorical_accuracy: 0.8926 - 489ms/epoch - 24ms/step
Epoch 949/1500
20/20 - 0s - loss: 0.2698 - categorical_accuracy: 0.9041 - val_loss: 0.3051 - val_categorical_accuracy: 0.8891 - 499ms/epoch - 25ms/step
Epoch 950/1500
20/20 - 1s - loss: 0.3135 - categorical_accuracy: 0.8843 - val_loss: 0.3403 - val_categorical_accuracy: 0.8738 - 502ms/epoch - 25ms/step
Epoch 951/1500
20/20 - 1s - loss: 0.2640 - categorical_accuracy: 0.9078 - val_loss: 0.2990 - val_categorical_accuracy: 0.8917 - 504ms/epoch - 25ms/step
Epoch 952/1500
20/20 - 1s - loss: 0.2742 - categorical_accuracy: 0.9030 - val_loss: 0.3008 - val_categorical_accuracy: 0.8913 - 517ms/epoch - 26ms/step
Epoch 953/1500
20/20 - 1s - loss: 0.2574 - categorical_accuracy: 0.9113 - val_loss: 0.2976 - val_categorical_accuracy: 0.8928 - 523ms/epoch - 26ms/step
Epoch 954/1500
20/20 - 0s - loss: 0.2724 - categorical_accuracy: 0.9038 - val_loss: 0.2768 - val_categorical_accuracy: 0.9022 - 499ms/epoch - 25ms/step
Epoch 955/1500
20/20 - 1s - loss: 0.3039 - categorical_accuracy: 0.8863 - val_loss: 0.3674 - val_categorical_accuracy: 0.8623 - 508ms/epoch - 25ms/step
Epoch 956/1500
20/20 - 1s - loss: 0.3727 - categorical_accuracy: 0.8843 - val_loss: 0.2661 - val_categorical_accuracy: 0.9090 - 502ms/epoch - 25ms/step
Epoch 957/1500
20/20 - 1s - loss: 0.2360 - categorical_accuracy: 0.9222 - val_loss: 0.2660 - val_categorical_accuracy: 0.9092 - 504ms/epoch - 25ms/step
Epoch 958/1500
20/20 - 0s - loss: 0.2491 - categorical_accuracy: 0.9145 - val_loss: 0.2986 - val_categorical_accuracy: 0.8944 - 496ms/epoch - 25ms/step
Epoch 959/1500
20/20 - 0s - loss: 0.2819 - categorical_accuracy: 0.8980 - val_loss: 0.2899 - val_categorical_accuracy: 0.8981 - 493ms/epoch - 25ms/step
Epoch 960/1500
20/20 - 1s - loss: 0.2737 - categorical_accuracy: 0.9016 - val_loss: 0.2917 - val_categorical_accuracy: 0.8981 - 500ms/epoch - 25ms/step
Epoch 961/1500
20/20 - 1s - loss: 0.2519 - categorical_accuracy: 0.9129 - val_loss: 0.2895 - val_categorical_accuracy: 0.8977 - 502ms/epoch - 25ms/step
Epoch 962/1500
20/20 - 0s - loss: 0.2761 - categorical_accuracy: 0.9011 - val_loss: 0.2798 - val_categorical_accuracy: 0.9013 - 492ms/epoch - 25ms/step
Epoch 963/1500
20/20 - 0s - loss: 0.2748 - categorical_accuracy: 0.8999 - val_loss: 0.3173 - val_categorical_accuracy: 0.8782 - 490ms/epoch - 25ms/step
Epoch 964/1500
20/20 - 0s - loss: 0.2794 - categorical_accuracy: 0.8971 - val_loss: 0.3008 - val_categorical_accuracy: 0.8892 - 495ms/epoch - 25ms/step
Epoch 965/1500
20/20 - 0s - loss: 0.2647 - categorical_accuracy: 0.9049 - val_loss: 0.3018 - val_categorical_accuracy: 0.8885 - 498ms/epoch - 25ms/step
Epoch 966/1500
20/20 - 0s - loss: 0.2770 - categorical_accuracy: 0.8984 - val_loss: 0.2824 - val_categorical_accuracy: 0.9006 - 494ms/epoch - 25ms/step
Epoch 967/1500
20/20 - 1s - loss: 0.2523 - categorical_accuracy: 0.9121 - val_loss: 0.2729 - val_categorical_accuracy: 0.9064 - 502ms/epoch - 25ms/step
Epoch 968/1500
20/20 - 0s - loss: 0.2699 - categorical_accuracy: 0.9042 - val_loss: 0.3268 - val_categorical_accuracy: 0.8808 - 484ms/epoch - 24ms/step
Epoch 969/1500
20/20 - 0s - loss: 0.2977 - categorical_accuracy: 0.8924 - val_loss: 0.2940 - val_categorical_accuracy: 0.8973 - 486ms/epoch - 24ms/step
Epoch 970/1500
20/20 - 0s - loss: 0.2664 - categorical_accuracy: 0.9073 - val_loss: 0.3142 - val_categorical_accuracy: 0.8894 - 472ms/epoch - 24ms/step
Epoch 971/1500
20/20 - 0s - loss: 0.2740 - categorical_accuracy: 0.9032 - val_loss: 0.2848 - val_categorical_accuracy: 0.9001 - 489ms/epoch - 24ms/step
Epoch 972/1500
20/20 - 0s - loss: 0.2727 - categorical_accuracy: 0.9018 - val_loss: 0.3297 - val_categorical_accuracy: 0.8820 - 472ms/epoch - 24ms/step
Epoch 973/1500
20/20 - 0s - loss: 0.2728 - categorical_accuracy: 0.9028 - val_loss: 0.2980 - val_categorical_accuracy: 0.8939 - 484ms/epoch - 24ms/step
Epoch 974/1500
20/20 - 0s - loss: 0.2649 - categorical_accuracy: 0.9054 - val_loss: 0.2903 - val_categorical_accuracy: 0.8969 - 488ms/epoch - 24ms/step
Epoch 975/1500
20/20 - 0s - loss: 0.2630 - categorical_accuracy: 0.9065 - val_loss: 0.3422 - val_categorical_accuracy: 0.8721 - 472ms/epoch - 24ms/step
Epoch 976/1500
20/20 - 0s - loss: 0.2797 - categorical_accuracy: 0.8995 - val_loss: 0.2951 - val_categorical_accuracy: 0.8967 - 470ms/epoch - 24ms/step
Epoch 977/1500
20/20 - 0s - loss: 0.2596 - categorical_accuracy: 0.9101 - val_loss: 0.2963 - val_categorical_accuracy: 0.8946 - 480ms/epoch - 24ms/step
Epoch 978/1500
20/20 - 0s - loss: 0.2696 - categorical_accuracy: 0.9030 - val_loss: 0.3105 - val_categorical_accuracy: 0.8880 - 482ms/epoch - 24ms/step
Epoch 979/1500
20/20 - 0s - loss: 0.2584 - categorical_accuracy: 0.9090 - val_loss: 0.2805 - val_categorical_accuracy: 0.9028 - 478ms/epoch - 24ms/step
Epoch 980/1500
20/20 - 0s - loss: 0.2445 - categorical_accuracy: 0.9164 - val_loss: 0.2910 - val_categorical_accuracy: 0.8961 - 489ms/epoch - 24ms/step
Epoch 981/1500
20/20 - 0s - loss: 0.3994 - categorical_accuracy: 0.8649 - val_loss: 0.6846 - val_categorical_accuracy: 0.7886 - 479ms/epoch - 24ms/step
Epoch 982/1500
20/20 - 0s - loss: 0.9903 - categorical_accuracy: 0.7885 - val_loss: 0.3036 - val_categorical_accuracy: 0.8975 - 483ms/epoch - 24ms/step
Epoch 983/1500
20/20 - 0s - loss: 0.2653 - categorical_accuracy: 0.9137 - val_loss: 0.2848 - val_categorical_accuracy: 0.9038 - 466ms/epoch - 23ms/step
Epoch 984/1500
20/20 - 0s - loss: 0.2515 - categorical_accuracy: 0.9185 - val_loss: 0.2741 - val_categorical_accuracy: 0.9080 - 479ms/epoch - 24ms/step
Epoch 985/1500
20/20 - 0s - loss: 0.2433 - categorical_accuracy: 0.9212 - val_loss: 0.2690 - val_categorical_accuracy: 0.9092 - 488ms/epoch - 24ms/step
Epoch 986/1500
20/20 - 0s - loss: 0.2375 - categorical_accuracy: 0.9228 - val_loss: 0.2649 - val_categorical_accuracy: 0.9099 - 480ms/epoch - 24ms/step
Epoch 987/1500
20/20 - 0s - loss: 0.2377 - categorical_accuracy: 0.9212 - val_loss: 0.2634 - val_categorical_accuracy: 0.9098 - 483ms/epoch - 24ms/step
Epoch 988/1500
20/20 - 0s - loss: 0.2396 - categorical_accuracy: 0.9192 - val_loss: 0.2773 - val_categorical_accuracy: 0.9027 - 480ms/epoch - 24ms/step
Epoch 989/1500
20/20 - 0s - loss: 0.2763 - categorical_accuracy: 0.8990 - val_loss: 0.2838 - val_categorical_accuracy: 0.8997 - 474ms/epoch - 24ms/step
Epoch 990/1500
20/20 - 0s - loss: 0.2535 - categorical_accuracy: 0.9113 - val_loss: 0.2859 - val_categorical_accuracy: 0.8993 - 470ms/epoch - 24ms/step
Epoch 991/1500
20/20 - 0s - loss: 0.2554 - categorical_accuracy: 0.9102 - val_loss: 0.2887 - val_categorical_accuracy: 0.8978 - 468ms/epoch - 23ms/step
Epoch 992/1500
20/20 - 0s - loss: 0.2573 - categorical_accuracy: 0.9086 - val_loss: 0.2794 - val_categorical_accuracy: 0.9012 - 470ms/epoch - 24ms/step
Epoch 993/1500
20/20 - 0s - loss: 0.2512 - categorical_accuracy: 0.9118 - val_loss: 0.3223 - val_categorical_accuracy: 0.8821 - 475ms/epoch - 24ms/step
Epoch 994/1500
20/20 - 0s - loss: 0.3249 - categorical_accuracy: 0.8810 - val_loss: 0.2818 - val_categorical_accuracy: 0.9021 - 469ms/epoch - 23ms/step
Epoch 995/1500
20/20 - 0s - loss: 0.2540 - categorical_accuracy: 0.9109 - val_loss: 0.2634 - val_categorical_accuracy: 0.9098 - 470ms/epoch - 24ms/step
Epoch 996/1500
20/20 - 0s - loss: 0.2329 - categorical_accuracy: 0.9218 - val_loss: 0.2740 - val_categorical_accuracy: 0.9034 - 466ms/epoch - 23ms/step
Epoch 997/1500
20/20 - 0s - loss: 0.2703 - categorical_accuracy: 0.9012 - val_loss: 0.3115 - val_categorical_accuracy: 0.8803 - 472ms/epoch - 24ms/step
Epoch 998/1500
20/20 - 0s - loss: 0.2716 - categorical_accuracy: 0.9008 - val_loss: 0.2891 - val_categorical_accuracy: 0.8972 - 470ms/epoch - 24ms/step
Epoch 999/1500
20/20 - 0s - loss: 0.2529 - categorical_accuracy: 0.9113 - val_loss: 0.2790 - val_categorical_accuracy: 0.9005 - 469ms/epoch - 23ms/step
Epoch 1000/1500
20/20 - 0s - loss: 0.2877 - categorical_accuracy: 0.8944 - val_loss: 0.2780 - val_categorical_accuracy: 0.9015 - 490ms/epoch - 25ms/step
Epoch 1001/1500
20/20 - 0s - loss: 0.2362 - categorical_accuracy: 0.9205 - val_loss: 0.2834 - val_categorical_accuracy: 0.8987 - 485ms/epoch - 24ms/step
Epoch 1002/1500
20/20 - 0s - loss: 0.3254 - categorical_accuracy: 0.8805 - val_loss: 1.0099 - val_categorical_accuracy: 0.7954 - 488ms/epoch - 24ms/step
Epoch 1003/1500
20/20 - 0s - loss: 0.3945 - categorical_accuracy: 0.8767 - val_loss: 0.2602 - val_categorical_accuracy: 0.9128 - 486ms/epoch - 24ms/step
Epoch 1004/1500
20/20 - 0s - loss: 0.2297 - categorical_accuracy: 0.9245 - val_loss: 0.2587 - val_categorical_accuracy: 0.9108 - 470ms/epoch - 24ms/step
Epoch 1005/1500
20/20 - 0s - loss: 0.2308 - categorical_accuracy: 0.9231 - val_loss: 0.2917 - val_categorical_accuracy: 0.8950 - 468ms/epoch - 23ms/step
Epoch 1006/1500
20/20 - 0s - loss: 0.2678 - categorical_accuracy: 0.9038 - val_loss: 0.2920 - val_categorical_accuracy: 0.8956 - 485ms/epoch - 24ms/step
Epoch 1007/1500
20/20 - 0s - loss: 0.2587 - categorical_accuracy: 0.9083 - val_loss: 0.2885 - val_categorical_accuracy: 0.8965 - 488ms/epoch - 24ms/step
Epoch 1008/1500
20/20 - 1s - loss: 0.2318 - categorical_accuracy: 0.9221 - val_loss: 0.2565 - val_categorical_accuracy: 0.9115 - 503ms/epoch - 25ms/step
Epoch 1009/1500
20/20 - 1s - loss: 0.2277 - categorical_accuracy: 0.9242 - val_loss: 0.2937 - val_categorical_accuracy: 0.8951 - 510ms/epoch - 26ms/step
Epoch 1010/1500
20/20 - 0s - loss: 0.2731 - categorical_accuracy: 0.9017 - val_loss: 0.3326 - val_categorical_accuracy: 0.8789 - 499ms/epoch - 25ms/step
Epoch 1011/1500
20/20 - 1s - loss: 0.2868 - categorical_accuracy: 0.8951 - val_loss: 0.3609 - val_categorical_accuracy: 0.8631 - 500ms/epoch - 25ms/step
Epoch 1012/1500
20/20 - 1s - loss: 0.2895 - categorical_accuracy: 0.8913 - val_loss: 0.2872 - val_categorical_accuracy: 0.8954 - 510ms/epoch - 26ms/step
Epoch 1013/1500
20/20 - 1s - loss: 0.2513 - categorical_accuracy: 0.9118 - val_loss: 0.2751 - val_categorical_accuracy: 0.9028 - 511ms/epoch - 26ms/step
Epoch 1014/1500
20/20 - 0s - loss: 0.2513 - categorical_accuracy: 0.9119 - val_loss: 0.2920 - val_categorical_accuracy: 0.8961 - 495ms/epoch - 25ms/step
Epoch 1015/1500
20/20 - 0s - loss: 0.2549 - categorical_accuracy: 0.9103 - val_loss: 0.3276 - val_categorical_accuracy: 0.8795 - 496ms/epoch - 25ms/step
Epoch 1016/1500
20/20 - 0s - loss: 0.2927 - categorical_accuracy: 0.8906 - val_loss: 0.3143 - val_categorical_accuracy: 0.8878 - 489ms/epoch - 24ms/step
Epoch 1017/1500
20/20 - 1s - loss: 0.2526 - categorical_accuracy: 0.9108 - val_loss: 0.2642 - val_categorical_accuracy: 0.9080 - 502ms/epoch - 25ms/step
Epoch 1018/1500
20/20 - 0s - loss: 0.2265 - categorical_accuracy: 0.9242 - val_loss: 0.2610 - val_categorical_accuracy: 0.9087 - 491ms/epoch - 25ms/step
Epoch 1019/1500
20/20 - 0s - loss: 0.2710 - categorical_accuracy: 0.9028 - val_loss: 0.3050 - val_categorical_accuracy: 0.8893 - 499ms/epoch - 25ms/step
Epoch 1020/1500
20/20 - 1s - loss: 0.2457 - categorical_accuracy: 0.9153 - val_loss: 0.2622 - val_categorical_accuracy: 0.9089 - 504ms/epoch - 25ms/step
Epoch 1021/1500
20/20 - 0s - loss: 0.2267 - categorical_accuracy: 0.9243 - val_loss: 0.2773 - val_categorical_accuracy: 0.9018 - 488ms/epoch - 24ms/step
Epoch 1022/1500
20/20 - 0s - loss: 0.4127 - categorical_accuracy: 0.8613 - val_loss: 0.6833 - val_categorical_accuracy: 0.8056 - 485ms/epoch - 24ms/step
Epoch 1023/1500
20/20 - 0s - loss: 0.2785 - categorical_accuracy: 0.9095 - val_loss: 0.2530 - val_categorical_accuracy: 0.9145 - 481ms/epoch - 24ms/step
Epoch 1024/1500
20/20 - 0s - loss: 0.2222 - categorical_accuracy: 0.9272 - val_loss: 0.2503 - val_categorical_accuracy: 0.9144 - 485ms/epoch - 24ms/step
Epoch 1025/1500
20/20 - 0s - loss: 0.2300 - categorical_accuracy: 0.9230 - val_loss: 0.3187 - val_categorical_accuracy: 0.8828 - 486ms/epoch - 24ms/step
Epoch 1026/1500
20/20 - 0s - loss: 0.3004 - categorical_accuracy: 0.8870 - val_loss: 0.2689 - val_categorical_accuracy: 0.9057 - 489ms/epoch - 24ms/step
Epoch 1027/1500
20/20 - 0s - loss: 0.2333 - categorical_accuracy: 0.9204 - val_loss: 0.2909 - val_categorical_accuracy: 0.8963 - 484ms/epoch - 24ms/step
Epoch 1028/1500
20/20 - 0s - loss: 0.2588 - categorical_accuracy: 0.9076 - val_loss: 0.3161 - val_categorical_accuracy: 0.8854 - 491ms/epoch - 25ms/step
Epoch 1029/1500
20/20 - 0s - loss: 0.2711 - categorical_accuracy: 0.9025 - val_loss: 0.3177 - val_categorical_accuracy: 0.8836 - 484ms/epoch - 24ms/step
Epoch 1030/1500
20/20 - 1s - loss: 0.2462 - categorical_accuracy: 0.9152 - val_loss: 0.2640 - val_categorical_accuracy: 0.9064 - 501ms/epoch - 25ms/step
Epoch 1031/1500
20/20 - 0s - loss: 0.2403 - categorical_accuracy: 0.9169 - val_loss: 0.2641 - val_categorical_accuracy: 0.9065 - 469ms/epoch - 23ms/step
Epoch 1032/1500
20/20 - 0s - loss: 0.2463 - categorical_accuracy: 0.9143 - val_loss: 0.3052 - val_categorical_accuracy: 0.8883 - 475ms/epoch - 24ms/step
Epoch 1033/1500
20/20 - 0s - loss: 0.2781 - categorical_accuracy: 0.8985 - val_loss: 0.3324 - val_categorical_accuracy: 0.8712 - 468ms/epoch - 23ms/step
Epoch 1034/1500
20/20 - 0s - loss: 0.2925 - categorical_accuracy: 0.8887 - val_loss: 0.3062 - val_categorical_accuracy: 0.8839 - 473ms/epoch - 24ms/step
Epoch 1035/1500
20/20 - 0s - loss: 0.2523 - categorical_accuracy: 0.9100 - val_loss: 0.2758 - val_categorical_accuracy: 0.9006 - 460ms/epoch - 23ms/step
Epoch 1036/1500
20/20 - 0s - loss: 0.2407 - categorical_accuracy: 0.9162 - val_loss: 0.2507 - val_categorical_accuracy: 0.9142 - 480ms/epoch - 24ms/step
Epoch 1037/1500
20/20 - 0s - loss: 0.2183 - categorical_accuracy: 0.9284 - val_loss: 0.2535 - val_categorical_accuracy: 0.9142 - 480ms/epoch - 24ms/step
Epoch 1038/1500
20/20 - 0s - loss: 0.2533 - categorical_accuracy: 0.9114 - val_loss: 0.3208 - val_categorical_accuracy: 0.8824 - 477ms/epoch - 24ms/step
Epoch 1039/1500
20/20 - 0s - loss: 0.2814 - categorical_accuracy: 0.8977 - val_loss: 0.3012 - val_categorical_accuracy: 0.8912 - 491ms/epoch - 25ms/step
Epoch 1040/1500
20/20 - 0s - loss: 0.2442 - categorical_accuracy: 0.9154 - val_loss: 0.2750 - val_categorical_accuracy: 0.9030 - 470ms/epoch - 24ms/step
Epoch 1041/1500
20/20 - 0s - loss: 0.2557 - categorical_accuracy: 0.9070 - val_loss: 0.3263 - val_categorical_accuracy: 0.8745 - 469ms/epoch - 23ms/step
Epoch 1042/1500
20/20 - 0s - loss: 0.2666 - categorical_accuracy: 0.9019 - val_loss: 0.2587 - val_categorical_accuracy: 0.9100 - 466ms/epoch - 23ms/step
Epoch 1043/1500
20/20 - 0s - loss: 0.2339 - categorical_accuracy: 0.9186 - val_loss: 0.2590 - val_categorical_accuracy: 0.9094 - 476ms/epoch - 24ms/step
Epoch 1044/1500
20/20 - 0s - loss: 0.2361 - categorical_accuracy: 0.9181 - val_loss: 0.2943 - val_categorical_accuracy: 0.8896 - 467ms/epoch - 23ms/step
Epoch 1045/1500
20/20 - 0s - loss: 0.2634 - categorical_accuracy: 0.9039 - val_loss: 0.2812 - val_categorical_accuracy: 0.9023 - 480ms/epoch - 24ms/step
Epoch 1046/1500
20/20 - 0s - loss: 0.2476 - categorical_accuracy: 0.9149 - val_loss: 0.2572 - val_categorical_accuracy: 0.9123 - 485ms/epoch - 24ms/step
Epoch 1047/1500
20/20 - 0s - loss: 0.2530 - categorical_accuracy: 0.9105 - val_loss: 0.3434 - val_categorical_accuracy: 0.8735 - 480ms/epoch - 24ms/step
Epoch 1048/1500
20/20 - 0s - loss: 0.2849 - categorical_accuracy: 0.8969 - val_loss: 0.3186 - val_categorical_accuracy: 0.8839 - 469ms/epoch - 23ms/step
Epoch 1049/1500
20/20 - 0s - loss: 0.2355 - categorical_accuracy: 0.9190 - val_loss: 0.2638 - val_categorical_accuracy: 0.9084 - 474ms/epoch - 24ms/step
Epoch 1050/1500
20/20 - 0s - loss: 0.2403 - categorical_accuracy: 0.9150 - val_loss: 0.2736 - val_categorical_accuracy: 0.9013 - 472ms/epoch - 24ms/step
Epoch 1051/1500
20/20 - 0s - loss: 0.2684 - categorical_accuracy: 0.9014 - val_loss: 0.2650 - val_categorical_accuracy: 0.9066 - 467ms/epoch - 23ms/step
Epoch 1052/1500
20/20 - 0s - loss: 0.2367 - categorical_accuracy: 0.9179 - val_loss: 0.2886 - val_categorical_accuracy: 0.8956 - 479ms/epoch - 24ms/step
Epoch 1053/1500
20/20 - 0s - loss: 0.2484 - categorical_accuracy: 0.9129 - val_loss: 0.2621 - val_categorical_accuracy: 0.9099 - 485ms/epoch - 24ms/step
Epoch 1054/1500
20/20 - 0s - loss: 0.2320 - categorical_accuracy: 0.9220 - val_loss: 0.2519 - val_categorical_accuracy: 0.9136 - 475ms/epoch - 24ms/step
Epoch 1055/1500
20/20 - 0s - loss: 0.2621 - categorical_accuracy: 0.9056 - val_loss: 0.3200 - val_categorical_accuracy: 0.8855 - 471ms/epoch - 24ms/step
Epoch 1056/1500
20/20 - 0s - loss: 0.2434 - categorical_accuracy: 0.9151 - val_loss: 0.2685 - val_categorical_accuracy: 0.9047 - 476ms/epoch - 24ms/step
Epoch 1057/1500
20/20 - 0s - loss: 0.2321 - categorical_accuracy: 0.9199 - val_loss: 0.2941 - val_categorical_accuracy: 0.8942 - 468ms/epoch - 23ms/step
Epoch 1058/1500
20/20 - 0s - loss: 0.4300 - categorical_accuracy: 0.8689 - val_loss: 0.2524 - val_categorical_accuracy: 0.9135 - 464ms/epoch - 23ms/step
Epoch 1059/1500
20/20 - 0s - loss: 0.2173 - categorical_accuracy: 0.9289 - val_loss: 0.2514 - val_categorical_accuracy: 0.9146 - 476ms/epoch - 24ms/step
Epoch 1060/1500
20/20 - 0s - loss: 0.2145 - categorical_accuracy: 0.9298 - val_loss: 0.2480 - val_categorical_accuracy: 0.9160 - 483ms/epoch - 24ms/step
Epoch 1061/1500
20/20 - 0s - loss: 0.2349 - categorical_accuracy: 0.9191 - val_loss: 0.3122 - val_categorical_accuracy: 0.8848 - 478ms/epoch - 24ms/step
Epoch 1062/1500
20/20 - 0s - loss: 0.2625 - categorical_accuracy: 0.9058 - val_loss: 0.2667 - val_categorical_accuracy: 0.9073 - 481ms/epoch - 24ms/step
Epoch 1063/1500
20/20 - 0s - loss: 0.2662 - categorical_accuracy: 0.9037 - val_loss: 0.3208 - val_categorical_accuracy: 0.8827 - 474ms/epoch - 24ms/step
Epoch 1064/1500
20/20 - 0s - loss: 0.2811 - categorical_accuracy: 0.8948 - val_loss: 0.2799 - val_categorical_accuracy: 0.8998 - 469ms/epoch - 23ms/step
Epoch 1065/1500
20/20 - 0s - loss: 0.2392 - categorical_accuracy: 0.9166 - val_loss: 0.2570 - val_categorical_accuracy: 0.9099 - 485ms/epoch - 24ms/step
Epoch 1066/1500
20/20 - 0s - loss: 0.2256 - categorical_accuracy: 0.9232 - val_loss: 0.2594 - val_categorical_accuracy: 0.9082 - 491ms/epoch - 25ms/step
Epoch 1067/1500
20/20 - 1s - loss: 0.2324 - categorical_accuracy: 0.9193 - val_loss: 0.2694 - val_categorical_accuracy: 0.9052 - 503ms/epoch - 25ms/step
Epoch 1068/1500
20/20 - 0s - loss: 0.2495 - categorical_accuracy: 0.9103 - val_loss: 0.2714 - val_categorical_accuracy: 0.9039 - 486ms/epoch - 24ms/step
Epoch 1069/1500
20/20 - 0s - loss: 0.2498 - categorical_accuracy: 0.9096 - val_loss: 0.2913 - val_categorical_accuracy: 0.8958 - 492ms/epoch - 25ms/step
Epoch 1070/1500
20/20 - 0s - loss: 0.2698 - categorical_accuracy: 0.9018 - val_loss: 0.3226 - val_categorical_accuracy: 0.8816 - 484ms/epoch - 24ms/step
Epoch 1071/1500
20/20 - 0s - loss: 0.2509 - categorical_accuracy: 0.9112 - val_loss: 0.2881 - val_categorical_accuracy: 0.8977 - 489ms/epoch - 24ms/step
Epoch 1072/1500
20/20 - 0s - loss: 0.2327 - categorical_accuracy: 0.9192 - val_loss: 0.2663 - val_categorical_accuracy: 0.9054 - 478ms/epoch - 24ms/step
Epoch 1073/1500
20/20 - 1s - loss: 0.2627 - categorical_accuracy: 0.9037 - val_loss: 0.2673 - val_categorical_accuracy: 0.9055 - 764ms/epoch - 38ms/step
Epoch 1074/1500
20/20 - 0s - loss: 0.2233 - categorical_accuracy: 0.9237 - val_loss: 0.2560 - val_categorical_accuracy: 0.9135 - 472ms/epoch - 24ms/step
Epoch 1075/1500
20/20 - 0s - loss: 0.2346 - categorical_accuracy: 0.9197 - val_loss: 0.2590 - val_categorical_accuracy: 0.9098 - 488ms/epoch - 24ms/step
Epoch 1076/1500
20/20 - 0s - loss: 0.2435 - categorical_accuracy: 0.9136 - val_loss: 0.3155 - val_categorical_accuracy: 0.8806 - 479ms/epoch - 24ms/step
Epoch 1077/1500
20/20 - 0s - loss: 0.2728 - categorical_accuracy: 0.8986 - val_loss: 0.3072 - val_categorical_accuracy: 0.8870 - 482ms/epoch - 24ms/step
Epoch 1078/1500
20/20 - 0s - loss: 0.2594 - categorical_accuracy: 0.9068 - val_loss: 0.2567 - val_categorical_accuracy: 0.9092 - 489ms/epoch - 24ms/step
Epoch 1079/1500
20/20 - 0s - loss: 0.2249 - categorical_accuracy: 0.9240 - val_loss: 0.2943 - val_categorical_accuracy: 0.8942 - 479ms/epoch - 24ms/step
Epoch 1080/1500
20/20 - 0s - loss: 0.2439 - categorical_accuracy: 0.9148 - val_loss: 0.2519 - val_categorical_accuracy: 0.9129 - 477ms/epoch - 24ms/step
Epoch 1081/1500
20/20 - 0s - loss: 0.2326 - categorical_accuracy: 0.9192 - val_loss: 0.2743 - val_categorical_accuracy: 0.9012 - 468ms/epoch - 23ms/step
Epoch 1082/1500
20/20 - 0s - loss: 0.2404 - categorical_accuracy: 0.9155 - val_loss: 0.2730 - val_categorical_accuracy: 0.9018 - 474ms/epoch - 24ms/step
Epoch 1083/1500
20/20 - 0s - loss: 0.2500 - categorical_accuracy: 0.9113 - val_loss: 0.2837 - val_categorical_accuracy: 0.8982 - 484ms/epoch - 24ms/step
Epoch 1084/1500
20/20 - 0s - loss: 0.2375 - categorical_accuracy: 0.9166 - val_loss: 0.2852 - val_categorical_accuracy: 0.8983 - 481ms/epoch - 24ms/step
Epoch 1085/1500
20/20 - 0s - loss: 0.2649 - categorical_accuracy: 0.9028 - val_loss: 0.3891 - val_categorical_accuracy: 0.8583 - 481ms/epoch - 24ms/step
Epoch 1086/1500
20/20 - 0s - loss: 0.4605 - categorical_accuracy: 0.8616 - val_loss: 0.2469 - val_categorical_accuracy: 0.9162 - 470ms/epoch - 24ms/step
Epoch 1087/1500
20/20 - 1s - loss: 0.2121 - categorical_accuracy: 0.9314 - val_loss: 0.2410 - val_categorical_accuracy: 0.9179 - 502ms/epoch - 25ms/step
Epoch 1088/1500
20/20 - 0s - loss: 0.2191 - categorical_accuracy: 0.9263 - val_loss: 0.2549 - val_categorical_accuracy: 0.9104 - 495ms/epoch - 25ms/step
Epoch 1089/1500
20/20 - 1s - loss: 0.2242 - categorical_accuracy: 0.9229 - val_loss: 0.2766 - val_categorical_accuracy: 0.9013 - 501ms/epoch - 25ms/step
Epoch 1090/1500
20/20 - 0s - loss: 0.2413 - categorical_accuracy: 0.9144 - val_loss: 0.2974 - val_categorical_accuracy: 0.8918 - 493ms/epoch - 25ms/step
Epoch 1091/1500
20/20 - 0s - loss: 0.2677 - categorical_accuracy: 0.9015 - val_loss: 0.2706 - val_categorical_accuracy: 0.9054 - 498ms/epoch - 25ms/step
Epoch 1092/1500
20/20 - 0s - loss: 0.2367 - categorical_accuracy: 0.9180 - val_loss: 0.2638 - val_categorical_accuracy: 0.9079 - 490ms/epoch - 25ms/step
Epoch 1093/1500
20/20 - 0s - loss: 0.2215 - categorical_accuracy: 0.9244 - val_loss: 0.2518 - val_categorical_accuracy: 0.9136 - 487ms/epoch - 24ms/step
Epoch 1094/1500
20/20 - 0s - loss: 0.2402 - categorical_accuracy: 0.9164 - val_loss: 0.2712 - val_categorical_accuracy: 0.9062 - 490ms/epoch - 25ms/step
Epoch 1095/1500
20/20 - 0s - loss: 0.2368 - categorical_accuracy: 0.9171 - val_loss: 0.3160 - val_categorical_accuracy: 0.8842 - 498ms/epoch - 25ms/step
Epoch 1096/1500
20/20 - 1s - loss: 0.2720 - categorical_accuracy: 0.8984 - val_loss: 0.2664 - val_categorical_accuracy: 0.9053 - 504ms/epoch - 25ms/step
Epoch 1097/1500
20/20 - 1s - loss: 0.2305 - categorical_accuracy: 0.9195 - val_loss: 0.2893 - val_categorical_accuracy: 0.8965 - 520ms/epoch - 26ms/step
Epoch 1098/1500
20/20 - 1s - loss: 0.2198 - categorical_accuracy: 0.9252 - val_loss: 0.2562 - val_categorical_accuracy: 0.9093 - 503ms/epoch - 25ms/step
Epoch 1099/1500
20/20 - 1s - loss: 0.2374 - categorical_accuracy: 0.9171 - val_loss: 0.2537 - val_categorical_accuracy: 0.9111 - 516ms/epoch - 26ms/step
Epoch 1100/1500
20/20 - 1s - loss: 0.2632 - categorical_accuracy: 0.9049 - val_loss: 0.2996 - val_categorical_accuracy: 0.8900 - 511ms/epoch - 26ms/step
Epoch 1101/1500
20/20 - 1s - loss: 0.2475 - categorical_accuracy: 0.9113 - val_loss: 0.3006 - val_categorical_accuracy: 0.8883 - 502ms/epoch - 25ms/step
Epoch 1102/1500
20/20 - 1s - loss: 0.2704 - categorical_accuracy: 0.8993 - val_loss: 0.2909 - val_categorical_accuracy: 0.8899 - 513ms/epoch - 26ms/step
Epoch 1103/1500
20/20 - 1s - loss: 0.2215 - categorical_accuracy: 0.9234 - val_loss: 0.2377 - val_categorical_accuracy: 0.9200 - 506ms/epoch - 25ms/step
Epoch 1104/1500
20/20 - 1s - loss: 0.2088 - categorical_accuracy: 0.9308 - val_loss: 0.2535 - val_categorical_accuracy: 0.9122 - 518ms/epoch - 26ms/step
Epoch 1105/1500
20/20 - 0s - loss: 0.2371 - categorical_accuracy: 0.9159 - val_loss: 0.2911 - val_categorical_accuracy: 0.8947 - 497ms/epoch - 25ms/step
Epoch 1106/1500
20/20 - 0s - loss: 0.2456 - categorical_accuracy: 0.9124 - val_loss: 0.2530 - val_categorical_accuracy: 0.9133 - 475ms/epoch - 24ms/step
Epoch 1107/1500
20/20 - 0s - loss: 0.2199 - categorical_accuracy: 0.9251 - val_loss: 0.2588 - val_categorical_accuracy: 0.9084 - 486ms/epoch - 24ms/step
Epoch 1108/1500
20/20 - 0s - loss: 0.2511 - categorical_accuracy: 0.9083 - val_loss: 0.3148 - val_categorical_accuracy: 0.8791 - 471ms/epoch - 24ms/step
Epoch 1109/1500
20/20 - 0s - loss: 0.2720 - categorical_accuracy: 0.9014 - val_loss: 0.3997 - val_categorical_accuracy: 0.8597 - 479ms/epoch - 24ms/step
Epoch 1110/1500
20/20 - 0s - loss: 0.4583 - categorical_accuracy: 0.8662 - val_loss: 0.2435 - val_categorical_accuracy: 0.9174 - 472ms/epoch - 24ms/step
Epoch 1111/1500
20/20 - 0s - loss: 0.2104 - categorical_accuracy: 0.9313 - val_loss: 0.2571 - val_categorical_accuracy: 0.9110 - 478ms/epoch - 24ms/step
Epoch 1112/1500
20/20 - 0s - loss: 0.2256 - categorical_accuracy: 0.9224 - val_loss: 0.2421 - val_categorical_accuracy: 0.9174 - 477ms/epoch - 24ms/step
Epoch 1113/1500
20/20 - 0s - loss: 0.2088 - categorical_accuracy: 0.9311 - val_loss: 0.2467 - val_categorical_accuracy: 0.9156 - 483ms/epoch - 24ms/step
Epoch 1114/1500
20/20 - 0s - loss: 0.2261 - categorical_accuracy: 0.9215 - val_loss: 0.2390 - val_categorical_accuracy: 0.9177 - 478ms/epoch - 24ms/step
Epoch 1115/1500
20/20 - 0s - loss: 0.2302 - categorical_accuracy: 0.9186 - val_loss: 0.2722 - val_categorical_accuracy: 0.9010 - 489ms/epoch - 24ms/step
Epoch 1116/1500
20/20 - 0s - loss: 0.2583 - categorical_accuracy: 0.9046 - val_loss: 0.2561 - val_categorical_accuracy: 0.9099 - 476ms/epoch - 24ms/step
Epoch 1117/1500
20/20 - 0s - loss: 0.2216 - categorical_accuracy: 0.9239 - val_loss: 0.2735 - val_categorical_accuracy: 0.9032 - 478ms/epoch - 24ms/step
Epoch 1118/1500
20/20 - 0s - loss: 0.2729 - categorical_accuracy: 0.9001 - val_loss: 0.2697 - val_categorical_accuracy: 0.9054 - 472ms/epoch - 24ms/step
Epoch 1119/1500
20/20 - 0s - loss: 0.2260 - categorical_accuracy: 0.9227 - val_loss: 0.2615 - val_categorical_accuracy: 0.9087 - 471ms/epoch - 24ms/step
Epoch 1120/1500
20/20 - 0s - loss: 0.2104 - categorical_accuracy: 0.9296 - val_loss: 0.2516 - val_categorical_accuracy: 0.9126 - 480ms/epoch - 24ms/step
Epoch 1121/1500
20/20 - 0s - loss: 0.2343 - categorical_accuracy: 0.9171 - val_loss: 0.2758 - val_categorical_accuracy: 0.8981 - 494ms/epoch - 25ms/step
Epoch 1122/1500
20/20 - 0s - loss: 0.2264 - categorical_accuracy: 0.9205 - val_loss: 0.2343 - val_categorical_accuracy: 0.9206 - 480ms/epoch - 24ms/step
Epoch 1123/1500
20/20 - 0s - loss: 0.2371 - categorical_accuracy: 0.9150 - val_loss: 0.3488 - val_categorical_accuracy: 0.8671 - 489ms/epoch - 24ms/step
Epoch 1124/1500
20/20 - 0s - loss: 0.2826 - categorical_accuracy: 0.8955 - val_loss: 0.2797 - val_categorical_accuracy: 0.8981 - 499ms/epoch - 25ms/step
Epoch 1125/1500
20/20 - 1s - loss: 0.2377 - categorical_accuracy: 0.9168 - val_loss: 0.2403 - val_categorical_accuracy: 0.9168 - 504ms/epoch - 25ms/step
Epoch 1126/1500
20/20 - 1s - loss: 0.2225 - categorical_accuracy: 0.9237 - val_loss: 0.2427 - val_categorical_accuracy: 0.9155 - 503ms/epoch - 25ms/step
Epoch 1127/1500
20/20 - 1s - loss: 0.2188 - categorical_accuracy: 0.9251 - val_loss: 0.2685 - val_categorical_accuracy: 0.9037 - 504ms/epoch - 25ms/step
Epoch 1128/1500
20/20 - 1s - loss: 0.2307 - categorical_accuracy: 0.9194 - val_loss: 0.2874 - val_categorical_accuracy: 0.8963 - 502ms/epoch - 25ms/step
Epoch 1129/1500
20/20 - 1s - loss: 0.2427 - categorical_accuracy: 0.9145 - val_loss: 0.2369 - val_categorical_accuracy: 0.9184 - 507ms/epoch - 25ms/step
Epoch 1130/1500
20/20 - 1s - loss: 0.2044 - categorical_accuracy: 0.9325 - val_loss: 0.2358 - val_categorical_accuracy: 0.9201 - 505ms/epoch - 25ms/step
Epoch 1131/1500
20/20 - 0s - loss: 0.2409 - categorical_accuracy: 0.9134 - val_loss: 0.2894 - val_categorical_accuracy: 0.8894 - 499ms/epoch - 25ms/step
Epoch 1132/1500
20/20 - 1s - loss: 0.2752 - categorical_accuracy: 0.8953 - val_loss: 0.2792 - val_categorical_accuracy: 0.8984 - 502ms/epoch - 25ms/step
Epoch 1133/1500
20/20 - 0s - loss: 0.2200 - categorical_accuracy: 0.9254 - val_loss: 0.2333 - val_categorical_accuracy: 0.9208 - 490ms/epoch - 25ms/step
Epoch 1134/1500
20/20 - 0s - loss: 0.2036 - categorical_accuracy: 0.9326 - val_loss: 0.2423 - val_categorical_accuracy: 0.9174 - 489ms/epoch - 24ms/step
Epoch 1135/1500
20/20 - 0s - loss: 0.2482 - categorical_accuracy: 0.9112 - val_loss: 0.3317 - val_categorical_accuracy: 0.8787 - 487ms/epoch - 24ms/step
Epoch 1136/1500
20/20 - 0s - loss: 0.2488 - categorical_accuracy: 0.9109 - val_loss: 0.2526 - val_categorical_accuracy: 0.9128 - 481ms/epoch - 24ms/step
Epoch 1137/1500
20/20 - 0s - loss: 0.2215 - categorical_accuracy: 0.9241 - val_loss: 0.2772 - val_categorical_accuracy: 0.9049 - 482ms/epoch - 24ms/step
Epoch 1138/1500
20/20 - 0s - loss: 1.1829 - categorical_accuracy: 0.7806 - val_loss: 0.3039 - val_categorical_accuracy: 0.8976 - 478ms/epoch - 24ms/step
Epoch 1139/1500
20/20 - 0s - loss: 0.2478 - categorical_accuracy: 0.9207 - val_loss: 0.2635 - val_categorical_accuracy: 0.9127 - 478ms/epoch - 24ms/step
Epoch 1140/1500
20/20 - 0s - loss: 0.2274 - categorical_accuracy: 0.9274 - val_loss: 0.2513 - val_categorical_accuracy: 0.9164 - 483ms/epoch - 24ms/step
Epoch 1141/1500
20/20 - 0s - loss: 0.2176 - categorical_accuracy: 0.9303 - val_loss: 0.2461 - val_categorical_accuracy: 0.9179 - 472ms/epoch - 24ms/step
Epoch 1142/1500
20/20 - 0s - loss: 0.2109 - categorical_accuracy: 0.9323 - val_loss: 0.2387 - val_categorical_accuracy: 0.9200 - 483ms/epoch - 24ms/step
Epoch 1143/1500
20/20 - 0s - loss: 0.2060 - categorical_accuracy: 0.9338 - val_loss: 0.2356 - val_categorical_accuracy: 0.9212 - 481ms/epoch - 24ms/step
Epoch 1144/1500
20/20 - 0s - loss: 0.2024 - categorical_accuracy: 0.9350 - val_loss: 0.2352 - val_categorical_accuracy: 0.9197 - 469ms/epoch - 23ms/step
Epoch 1145/1500
20/20 - 0s - loss: 0.2061 - categorical_accuracy: 0.9317 - val_loss: 0.2485 - val_categorical_accuracy: 0.9133 - 473ms/epoch - 24ms/step
Epoch 1146/1500
20/20 - 0s - loss: 0.2153 - categorical_accuracy: 0.9270 - val_loss: 0.2700 - val_categorical_accuracy: 0.9043 - 480ms/epoch - 24ms/step
Epoch 1147/1500
20/20 - 0s - loss: 0.2156 - categorical_accuracy: 0.9259 - val_loss: 0.2391 - val_categorical_accuracy: 0.9168 - 478ms/epoch - 24ms/step
Epoch 1148/1500
20/20 - 0s - loss: 0.2208 - categorical_accuracy: 0.9230 - val_loss: 0.3095 - val_categorical_accuracy: 0.8870 - 468ms/epoch - 23ms/step
Epoch 1149/1500
20/20 - 0s - loss: 0.2806 - categorical_accuracy: 0.8955 - val_loss: 0.2355 - val_categorical_accuracy: 0.9201 - 474ms/epoch - 24ms/step
Epoch 1150/1500
20/20 - 0s - loss: 0.1985 - categorical_accuracy: 0.9352 - val_loss: 0.2313 - val_categorical_accuracy: 0.9218 - 470ms/epoch - 23ms/step
Epoch 1151/1500
20/20 - 0s - loss: 0.2070 - categorical_accuracy: 0.9307 - val_loss: 0.2572 - val_categorical_accuracy: 0.9096 - 484ms/epoch - 24ms/step
Epoch 1152/1500
20/20 - 0s - loss: 0.2658 - categorical_accuracy: 0.9039 - val_loss: 0.2931 - val_categorical_accuracy: 0.8953 - 469ms/epoch - 23ms/step
Epoch 1153/1500
20/20 - 0s - loss: 0.2318 - categorical_accuracy: 0.9186 - val_loss: 0.2419 - val_categorical_accuracy: 0.9171 - 478ms/epoch - 24ms/step
Epoch 1154/1500
20/20 - 0s - loss: 0.2422 - categorical_accuracy: 0.9133 - val_loss: 0.3291 - val_categorical_accuracy: 0.8787 - 485ms/epoch - 24ms/step
Epoch 1155/1500
20/20 - 0s - loss: 0.2402 - categorical_accuracy: 0.9135 - val_loss: 0.2326 - val_categorical_accuracy: 0.9197 - 469ms/epoch - 23ms/step
Epoch 1156/1500
20/20 - 0s - loss: 0.2167 - categorical_accuracy: 0.9257 - val_loss: 0.2724 - val_categorical_accuracy: 0.9037 - 474ms/epoch - 24ms/step
Epoch 1157/1500
20/20 - 0s - loss: 0.2340 - categorical_accuracy: 0.9170 - val_loss: 0.2416 - val_categorical_accuracy: 0.9151 - 488ms/epoch - 24ms/step
Epoch 1158/1500
20/20 - 0s - loss: 0.2042 - categorical_accuracy: 0.9318 - val_loss: 0.2567 - val_categorical_accuracy: 0.9083 - 472ms/epoch - 24ms/step
Epoch 1159/1500
20/20 - 0s - loss: 0.2693 - categorical_accuracy: 0.9024 - val_loss: 0.3537 - val_categorical_accuracy: 0.8700 - 471ms/epoch - 24ms/step
Epoch 1160/1500
20/20 - 0s - loss: 0.2577 - categorical_accuracy: 0.9059 - val_loss: 0.2944 - val_categorical_accuracy: 0.8878 - 474ms/epoch - 24ms/step
Epoch 1161/1500
20/20 - 0s - loss: 0.2288 - categorical_accuracy: 0.9191 - val_loss: 0.2372 - val_categorical_accuracy: 0.9194 - 487ms/epoch - 24ms/step
Epoch 1162/1500
20/20 - 0s - loss: 0.2030 - categorical_accuracy: 0.9321 - val_loss: 0.2404 - val_categorical_accuracy: 0.9180 - 482ms/epoch - 24ms/step
Epoch 1163/1500
20/20 - 0s - loss: 0.2265 - categorical_accuracy: 0.9201 - val_loss: 0.2660 - val_categorical_accuracy: 0.9017 - 472ms/epoch - 24ms/step
Epoch 1164/1500
20/20 - 0s - loss: 0.2127 - categorical_accuracy: 0.9266 - val_loss: 0.2347 - val_categorical_accuracy: 0.9190 - 474ms/epoch - 24ms/step
Epoch 1165/1500
20/20 - 0s - loss: 0.2302 - categorical_accuracy: 0.9199 - val_loss: 0.3208 - val_categorical_accuracy: 0.8821 - 479ms/epoch - 24ms/step
Epoch 1166/1500
20/20 - 0s - loss: 0.2607 - categorical_accuracy: 0.9058 - val_loss: 0.2368 - val_categorical_accuracy: 0.9188 - 475ms/epoch - 24ms/step
Epoch 1167/1500
20/20 - 0s - loss: 0.2142 - categorical_accuracy: 0.9265 - val_loss: 0.2474 - val_categorical_accuracy: 0.9129 - 489ms/epoch - 24ms/step
Epoch 1168/1500
20/20 - 0s - loss: 0.2293 - categorical_accuracy: 0.9186 - val_loss: 0.2860 - val_categorical_accuracy: 0.8924 - 477ms/epoch - 24ms/step
Epoch 1169/1500
20/20 - 0s - loss: 0.2310 - categorical_accuracy: 0.9177 - val_loss: 0.2707 - val_categorical_accuracy: 0.8991 - 474ms/epoch - 24ms/step
Epoch 1170/1500
20/20 - 0s - loss: 0.2242 - categorical_accuracy: 0.9205 - val_loss: 0.2361 - val_categorical_accuracy: 0.9195 - 462ms/epoch - 23ms/step
Epoch 1171/1500
20/20 - 0s - loss: 0.2161 - categorical_accuracy: 0.9260 - val_loss: 0.2416 - val_categorical_accuracy: 0.9178 - 474ms/epoch - 24ms/step
Epoch 1172/1500
20/20 - 0s - loss: 0.2160 - categorical_accuracy: 0.9248 - val_loss: 0.2616 - val_categorical_accuracy: 0.9079 - 466ms/epoch - 23ms/step
Epoch 1173/1500
20/20 - 0s - loss: 0.2182 - categorical_accuracy: 0.9252 - val_loss: 0.2449 - val_categorical_accuracy: 0.9151 - 474ms/epoch - 24ms/step
Epoch 1174/1500
20/20 - 0s - loss: 0.2237 - categorical_accuracy: 0.9216 - val_loss: 0.2615 - val_categorical_accuracy: 0.9086 - 466ms/epoch - 23ms/step
Epoch 1175/1500
20/20 - 0s - loss: 0.2196 - categorical_accuracy: 0.9240 - val_loss: 0.2853 - val_categorical_accuracy: 0.8999 - 472ms/epoch - 24ms/step
Epoch 1176/1500
20/20 - 0s - loss: 0.2308 - categorical_accuracy: 0.9194 - val_loss: 0.2552 - val_categorical_accuracy: 0.9116 - 472ms/epoch - 24ms/step
Epoch 1177/1500
20/20 - 0s - loss: 0.2087 - categorical_accuracy: 0.9289 - val_loss: 0.2385 - val_categorical_accuracy: 0.9184 - 486ms/epoch - 24ms/step
Epoch 1178/1500
20/20 - 0s - loss: 0.2618 - categorical_accuracy: 0.9028 - val_loss: 0.4046 - val_categorical_accuracy: 0.8523 - 476ms/epoch - 24ms/step
Epoch 1179/1500
20/20 - 0s - loss: 0.2511 - categorical_accuracy: 0.9085 - val_loss: 0.2411 - val_categorical_accuracy: 0.9160 - 488ms/epoch - 24ms/step
Epoch 1180/1500
20/20 - 0s - loss: 0.1977 - categorical_accuracy: 0.9338 - val_loss: 0.2243 - val_categorical_accuracy: 0.9241 - 491ms/epoch - 25ms/step
Epoch 1181/1500
20/20 - 0s - loss: 0.1959 - categorical_accuracy: 0.9353 - val_loss: 0.2473 - val_categorical_accuracy: 0.9128 - 499ms/epoch - 25ms/step
Epoch 1182/1500
20/20 - 0s - loss: 0.2950 - categorical_accuracy: 0.8933 - val_loss: 2.3880 - val_categorical_accuracy: 0.7550 - 484ms/epoch - 24ms/step
Epoch 1183/1500
20/20 - 0s - loss: 0.8382 - categorical_accuracy: 0.8346 - val_loss: 0.2528 - val_categorical_accuracy: 0.9161 - 474ms/epoch - 24ms/step
Epoch 1184/1500
20/20 - 0s - loss: 0.2148 - categorical_accuracy: 0.9315 - val_loss: 0.2405 - val_categorical_accuracy: 0.9193 - 483ms/epoch - 24ms/step
Epoch 1185/1500
20/20 - 0s - loss: 0.2052 - categorical_accuracy: 0.9343 - val_loss: 0.2340 - val_categorical_accuracy: 0.9212 - 486ms/epoch - 24ms/step
Epoch 1186/1500
20/20 - 0s - loss: 0.1998 - categorical_accuracy: 0.9360 - val_loss: 0.2331 - val_categorical_accuracy: 0.9214 - 472ms/epoch - 24ms/step
Epoch 1187/1500
20/20 - 0s - loss: 0.1973 - categorical_accuracy: 0.9366 - val_loss: 0.2309 - val_categorical_accuracy: 0.9208 - 480ms/epoch - 24ms/step
Epoch 1188/1500
20/20 - 0s - loss: 0.1932 - categorical_accuracy: 0.9377 - val_loss: 0.2289 - val_categorical_accuracy: 0.9232 - 490ms/epoch - 25ms/step
Epoch 1189/1500
20/20 - 0s - loss: 0.2171 - categorical_accuracy: 0.9254 - val_loss: 0.2860 - val_categorical_accuracy: 0.8976 - 484ms/epoch - 24ms/step
Epoch 1190/1500
20/20 - 0s - loss: 0.2598 - categorical_accuracy: 0.9063 - val_loss: 0.2414 - val_categorical_accuracy: 0.9172 - 486ms/epoch - 24ms/step
Epoch 1191/1500
20/20 - 0s - loss: 0.1956 - categorical_accuracy: 0.9354 - val_loss: 0.2519 - val_categorical_accuracy: 0.9106 - 490ms/epoch - 25ms/step
Epoch 1192/1500
20/20 - 0s - loss: 0.2340 - categorical_accuracy: 0.9157 - val_loss: 0.2683 - val_categorical_accuracy: 0.9006 - 475ms/epoch - 24ms/step
Epoch 1193/1500
20/20 - 0s - loss: 0.2242 - categorical_accuracy: 0.9201 - val_loss: 0.2528 - val_categorical_accuracy: 0.9092 - 483ms/epoch - 24ms/step
Epoch 1194/1500
20/20 - 0s - loss: 0.1953 - categorical_accuracy: 0.9354 - val_loss: 0.2271 - val_categorical_accuracy: 0.9220 - 482ms/epoch - 24ms/step
Epoch 1195/1500
20/20 - 0s - loss: 0.2598 - categorical_accuracy: 0.9078 - val_loss: 0.3438 - val_categorical_accuracy: 0.8762 - 497ms/epoch - 25ms/step
Epoch 1196/1500
20/20 - 1s - loss: 0.2368 - categorical_accuracy: 0.9172 - val_loss: 0.2219 - val_categorical_accuracy: 0.9249 - 500ms/epoch - 25ms/step
Epoch 1197/1500
20/20 - 1s - loss: 0.1902 - categorical_accuracy: 0.9381 - val_loss: 0.2340 - val_categorical_accuracy: 0.9205 - 502ms/epoch - 25ms/step
Epoch 1198/1500
20/20 - 1s - loss: 0.2245 - categorical_accuracy: 0.9206 - val_loss: 0.2726 - val_categorical_accuracy: 0.9028 - 518ms/epoch - 26ms/step
Epoch 1199/1500
20/20 - 1s - loss: 0.2203 - categorical_accuracy: 0.9231 - val_loss: 0.2610 - val_categorical_accuracy: 0.9040 - 518ms/epoch - 26ms/step
Epoch 1200/1500
20/20 - 0s - loss: 0.2638 - categorical_accuracy: 0.9013 - val_loss: 0.2306 - val_categorical_accuracy: 0.9212 - 488ms/epoch - 24ms/step
Epoch 1201/1500
20/20 - 0s - loss: 0.1907 - categorical_accuracy: 0.9374 - val_loss: 0.2304 - val_categorical_accuracy: 0.9220 - 472ms/epoch - 24ms/step
Epoch 1202/1500
20/20 - 0s - loss: 0.3709 - categorical_accuracy: 0.8938 - val_loss: 0.8424 - val_categorical_accuracy: 0.8081 - 481ms/epoch - 24ms/step
Epoch 1203/1500
20/20 - 0s - loss: 0.2562 - categorical_accuracy: 0.9200 - val_loss: 0.2248 - val_categorical_accuracy: 0.9235 - 473ms/epoch - 24ms/step
Epoch 1204/1500
20/20 - 0s - loss: 0.1901 - categorical_accuracy: 0.9385 - val_loss: 0.2212 - val_categorical_accuracy: 0.9262 - 473ms/epoch - 24ms/step
Epoch 1205/1500
20/20 - 0s - loss: 0.1929 - categorical_accuracy: 0.9363 - val_loss: 0.2347 - val_categorical_accuracy: 0.9182 - 474ms/epoch - 24ms/step
Epoch 1206/1500
20/20 - 0s - loss: 0.2324 - categorical_accuracy: 0.9158 - val_loss: 0.3458 - val_categorical_accuracy: 0.8737 - 473ms/epoch - 24ms/step
Epoch 1207/1500
20/20 - 0s - loss: 0.2532 - categorical_accuracy: 0.9067 - val_loss: 0.2259 - val_categorical_accuracy: 0.9229 - 485ms/epoch - 24ms/step
Epoch 1208/1500
20/20 - 0s - loss: 0.1869 - categorical_accuracy: 0.9396 - val_loss: 0.2221 - val_categorical_accuracy: 0.9249 - 466ms/epoch - 23ms/step
Epoch 1209/1500
20/20 - 0s - loss: 0.1914 - categorical_accuracy: 0.9366 - val_loss: 0.2720 - val_categorical_accuracy: 0.9025 - 459ms/epoch - 23ms/step
Epoch 1210/1500
20/20 - 0s - loss: 0.2917 - categorical_accuracy: 0.8933 - val_loss: 0.3015 - val_categorical_accuracy: 0.8901 - 463ms/epoch - 23ms/step
Epoch 1211/1500
20/20 - 0s - loss: 0.2176 - categorical_accuracy: 0.9242 - val_loss: 0.2444 - val_categorical_accuracy: 0.9139 - 468ms/epoch - 23ms/step
Epoch 1212/1500
20/20 - 0s - loss: 0.2174 - categorical_accuracy: 0.9234 - val_loss: 0.2473 - val_categorical_accuracy: 0.9124 - 476ms/epoch - 24ms/step
Epoch 1213/1500
20/20 - 0s - loss: 0.2172 - categorical_accuracy: 0.9236 - val_loss: 0.2463 - val_categorical_accuracy: 0.9132 - 467ms/epoch - 23ms/step
Epoch 1214/1500
20/20 - 0s - loss: 0.2251 - categorical_accuracy: 0.9191 - val_loss: 0.2242 - val_categorical_accuracy: 0.9253 - 472ms/epoch - 24ms/step
Epoch 1215/1500
20/20 - 0s - loss: 0.1944 - categorical_accuracy: 0.9353 - val_loss: 0.2417 - val_categorical_accuracy: 0.9185 - 476ms/epoch - 24ms/step
Epoch 1216/1500
20/20 - 0s - loss: 0.2511 - categorical_accuracy: 0.9101 - val_loss: 0.3109 - val_categorical_accuracy: 0.8870 - 473ms/epoch - 24ms/step
Epoch 1217/1500
20/20 - 0s - loss: 0.2189 - categorical_accuracy: 0.9243 - val_loss: 0.2266 - val_categorical_accuracy: 0.9225 - 465ms/epoch - 23ms/step
Epoch 1218/1500
20/20 - 0s - loss: 0.1920 - categorical_accuracy: 0.9365 - val_loss: 0.2231 - val_categorical_accuracy: 0.9250 - 466ms/epoch - 23ms/step
Epoch 1219/1500
20/20 - 0s - loss: 0.2088 - categorical_accuracy: 0.9282 - val_loss: 0.2678 - val_categorical_accuracy: 0.9009 - 466ms/epoch - 23ms/step
Epoch 1220/1500
20/20 - 0s - loss: 0.2526 - categorical_accuracy: 0.9057 - val_loss: 0.2580 - val_categorical_accuracy: 0.9077 - 466ms/epoch - 23ms/step
Epoch 1221/1500
20/20 - 0s - loss: 0.2212 - categorical_accuracy: 0.9223 - val_loss: 0.2472 - val_categorical_accuracy: 0.9130 - 466ms/epoch - 23ms/step
Epoch 1222/1500
20/20 - 0s - loss: 0.2255 - categorical_accuracy: 0.9201 - val_loss: 0.2751 - val_categorical_accuracy: 0.9013 - 472ms/epoch - 24ms/step
Epoch 1223/1500
20/20 - 0s - loss: 0.2029 - categorical_accuracy: 0.9307 - val_loss: 0.2573 - val_categorical_accuracy: 0.9080 - 474ms/epoch - 24ms/step
Epoch 1224/1500
20/20 - 0s - loss: 0.2358 - categorical_accuracy: 0.9160 - val_loss: 0.2713 - val_categorical_accuracy: 0.9029 - 456ms/epoch - 23ms/step
Epoch 1225/1500
20/20 - 0s - loss: 0.2140 - categorical_accuracy: 0.9258 - val_loss: 0.2240 - val_categorical_accuracy: 0.9224 - 465ms/epoch - 23ms/step
Epoch 1226/1500
20/20 - 0s - loss: 0.1938 - categorical_accuracy: 0.9351 - val_loss: 0.2540 - val_categorical_accuracy: 0.9104 - 466ms/epoch - 23ms/step
Epoch 1227/1500
20/20 - 0s - loss: 0.2565 - categorical_accuracy: 0.9067 - val_loss: 0.2938 - val_categorical_accuracy: 0.8948 - 467ms/epoch - 23ms/step
Epoch 1228/1500
20/20 - 0s - loss: 0.2313 - categorical_accuracy: 0.9161 - val_loss: 0.2308 - val_categorical_accuracy: 0.9207 - 468ms/epoch - 23ms/step
Epoch 1229/1500
20/20 - 0s - loss: 0.1975 - categorical_accuracy: 0.9337 - val_loss: 0.2243 - val_categorical_accuracy: 0.9226 - 481ms/epoch - 24ms/step
Epoch 1230/1500
20/20 - 0s - loss: 0.1933 - categorical_accuracy: 0.9349 - val_loss: 0.2526 - val_categorical_accuracy: 0.9106 - 480ms/epoch - 24ms/step
Epoch 1231/1500
20/20 - 0s - loss: 0.2213 - categorical_accuracy: 0.9209 - val_loss: 0.2726 - val_categorical_accuracy: 0.9027 - 470ms/epoch - 24ms/step
Epoch 1232/1500
20/20 - 0s - loss: 0.2156 - categorical_accuracy: 0.9239 - val_loss: 0.2352 - val_categorical_accuracy: 0.9173 - 474ms/epoch - 24ms/step
Epoch 1233/1500
20/20 - 0s - loss: 0.1860 - categorical_accuracy: 0.9392 - val_loss: 0.2355 - val_categorical_accuracy: 0.9171 - 483ms/epoch - 24ms/step
Epoch 1234/1500
20/20 - 0s - loss: 0.2421 - categorical_accuracy: 0.9134 - val_loss: 0.2937 - val_categorical_accuracy: 0.8939 - 474ms/epoch - 24ms/step
Epoch 1235/1500
20/20 - 0s - loss: 0.2547 - categorical_accuracy: 0.9087 - val_loss: 0.2223 - val_categorical_accuracy: 0.9238 - 474ms/epoch - 24ms/step
Epoch 1236/1500
20/20 - 0s - loss: 0.1868 - categorical_accuracy: 0.9393 - val_loss: 0.2219 - val_categorical_accuracy: 0.9256 - 471ms/epoch - 24ms/step
Epoch 1237/1500
20/20 - 0s - loss: 0.2069 - categorical_accuracy: 0.9304 - val_loss: 0.3061 - val_categorical_accuracy: 0.8927 - 462ms/epoch - 23ms/step
Epoch 1238/1500
20/20 - 0s - loss: 0.7486 - categorical_accuracy: 0.8328 - val_loss: 0.2401 - val_categorical_accuracy: 0.9192 - 465ms/epoch - 23ms/step
Epoch 1239/1500
20/20 - 0s - loss: 0.1996 - categorical_accuracy: 0.9361 - val_loss: 0.2264 - val_categorical_accuracy: 0.9239 - 473ms/epoch - 24ms/step
Epoch 1240/1500
20/20 - 0s - loss: 0.1911 - categorical_accuracy: 0.9386 - val_loss: 0.2224 - val_categorical_accuracy: 0.9252 - 458ms/epoch - 23ms/step
Epoch 1241/1500
20/20 - 0s - loss: 0.1862 - categorical_accuracy: 0.9404 - val_loss: 0.2194 - val_categorical_accuracy: 0.9265 - 472ms/epoch - 24ms/step
Epoch 1242/1500
20/20 - 0s - loss: 0.1835 - categorical_accuracy: 0.9412 - val_loss: 0.2195 - val_categorical_accuracy: 0.9253 - 472ms/epoch - 24ms/step
Epoch 1243/1500
20/20 - 0s - loss: 0.1827 - categorical_accuracy: 0.9408 - val_loss: 0.2198 - val_categorical_accuracy: 0.9264 - 471ms/epoch - 24ms/step
Epoch 1244/1500
20/20 - 0s - loss: 0.1937 - categorical_accuracy: 0.9354 - val_loss: 0.2689 - val_categorical_accuracy: 0.9041 - 469ms/epoch - 23ms/step
Epoch 1245/1500
20/20 - 0s - loss: 0.2798 - categorical_accuracy: 0.8969 - val_loss: 0.2631 - val_categorical_accuracy: 0.9068 - 475ms/epoch - 24ms/step
Epoch 1246/1500
20/20 - 0s - loss: 0.2331 - categorical_accuracy: 0.9148 - val_loss: 0.2479 - val_categorical_accuracy: 0.9122 - 473ms/epoch - 24ms/step
Epoch 1247/1500
20/20 - 0s - loss: 0.2118 - categorical_accuracy: 0.9258 - val_loss: 0.2729 - val_categorical_accuracy: 0.9031 - 471ms/epoch - 24ms/step
Epoch 1248/1500
20/20 - 0s - loss: 0.2020 - categorical_accuracy: 0.9311 - val_loss: 0.2362 - val_categorical_accuracy: 0.9173 - 476ms/epoch - 24ms/step
Epoch 1249/1500
20/20 - 0s - loss: 0.2004 - categorical_accuracy: 0.9315 - val_loss: 0.2253 - val_categorical_accuracy: 0.9218 - 477ms/epoch - 24ms/step
Epoch 1250/1500
20/20 - 0s - loss: 0.1894 - categorical_accuracy: 0.9366 - val_loss: 0.2519 - val_categorical_accuracy: 0.9111 - 474ms/epoch - 24ms/step
Epoch 1251/1500
20/20 - 0s - loss: 0.2307 - categorical_accuracy: 0.9174 - val_loss: 0.3377 - val_categorical_accuracy: 0.8776 - 486ms/epoch - 24ms/step
Epoch 1252/1500
20/20 - 0s - loss: 0.2627 - categorical_accuracy: 0.9043 - val_loss: 0.2815 - val_categorical_accuracy: 0.8943 - 471ms/epoch - 24ms/step
Epoch 1253/1500
20/20 - 0s - loss: 0.2125 - categorical_accuracy: 0.9252 - val_loss: 0.2329 - val_categorical_accuracy: 0.9189 - 481ms/epoch - 24ms/step
Epoch 1254/1500
20/20 - 0s - loss: 0.1879 - categorical_accuracy: 0.9374 - val_loss: 0.2296 - val_categorical_accuracy: 0.9227 - 484ms/epoch - 24ms/step
Epoch 1255/1500
20/20 - 0s - loss: 0.2284 - categorical_accuracy: 0.9185 - val_loss: 0.2985 - val_categorical_accuracy: 0.8876 - 485ms/epoch - 24ms/step
Epoch 1256/1500
20/20 - 0s - loss: 0.2386 - categorical_accuracy: 0.9138 - val_loss: 0.2205 - val_categorical_accuracy: 0.9251 - 472ms/epoch - 24ms/step
Epoch 1257/1500
20/20 - 0s - loss: 0.1893 - categorical_accuracy: 0.9367 - val_loss: 0.2241 - val_categorical_accuracy: 0.9245 - 484ms/epoch - 24ms/step
Epoch 1258/1500
20/20 - 0s - loss: 0.2085 - categorical_accuracy: 0.9280 - val_loss: 0.2868 - val_categorical_accuracy: 0.8925 - 474ms/epoch - 24ms/step
Epoch 1259/1500
20/20 - 0s - loss: 0.2661 - categorical_accuracy: 0.8998 - val_loss: 0.2460 - val_categorical_accuracy: 0.9133 - 471ms/epoch - 24ms/step
Epoch 1260/1500
20/20 - 0s - loss: 0.2016 - categorical_accuracy: 0.9307 - val_loss: 0.2251 - val_categorical_accuracy: 0.9219 - 482ms/epoch - 24ms/step
Epoch 1261/1500
20/20 - 0s - loss: 0.1958 - categorical_accuracy: 0.9336 - val_loss: 0.2593 - val_categorical_accuracy: 0.9080 - 484ms/epoch - 24ms/step
Epoch 1262/1500
20/20 - 1s - loss: 0.2381 - categorical_accuracy: 0.9141 - val_loss: 0.2528 - val_categorical_accuracy: 0.9104 - 525ms/epoch - 26ms/step
Epoch 1263/1500
20/20 - 0s - loss: 0.2010 - categorical_accuracy: 0.9322 - val_loss: 0.2222 - val_categorical_accuracy: 0.9234 - 496ms/epoch - 25ms/step
Epoch 1264/1500
20/20 - 0s - loss: 0.1918 - categorical_accuracy: 0.9355 - val_loss: 0.2224 - val_categorical_accuracy: 0.9227 - 492ms/epoch - 25ms/step
Epoch 1265/1500
20/20 - 0s - loss: 0.2027 - categorical_accuracy: 0.9295 - val_loss: 0.2650 - val_categorical_accuracy: 0.9068 - 485ms/epoch - 24ms/step
Epoch 1266/1500
20/20 - 0s - loss: 0.2209 - categorical_accuracy: 0.9206 - val_loss: 0.2156 - val_categorical_accuracy: 0.9261 - 499ms/epoch - 25ms/step
Epoch 1267/1500
20/20 - 0s - loss: 0.1825 - categorical_accuracy: 0.9396 - val_loss: 0.2322 - val_categorical_accuracy: 0.9184 - 491ms/epoch - 25ms/step
Epoch 1268/1500
20/20 - 0s - loss: 0.1914 - categorical_accuracy: 0.9354 - val_loss: 0.2233 - val_categorical_accuracy: 0.9219 - 484ms/epoch - 24ms/step
Epoch 1269/1500
20/20 - 0s - loss: 0.1986 - categorical_accuracy: 0.9316 - val_loss: 0.2385 - val_categorical_accuracy: 0.9159 - 490ms/epoch - 25ms/step
Epoch 1270/1500
20/20 - 0s - loss: 0.2377 - categorical_accuracy: 0.9153 - val_loss: 0.3913 - val_categorical_accuracy: 0.8603 - 489ms/epoch - 24ms/step
Epoch 1271/1500
20/20 - 0s - loss: 0.2490 - categorical_accuracy: 0.9103 - val_loss: 0.2662 - val_categorical_accuracy: 0.9013 - 489ms/epoch - 24ms/step
Epoch 1272/1500
20/20 - 0s - loss: 0.2242 - categorical_accuracy: 0.9187 - val_loss: 0.2570 - val_categorical_accuracy: 0.9058 - 486ms/epoch - 24ms/step
Epoch 1273/1500
20/20 - 0s - loss: 0.2011 - categorical_accuracy: 0.9304 - val_loss: 0.2197 - val_categorical_accuracy: 0.9253 - 495ms/epoch - 25ms/step
Epoch 1274/1500
20/20 - 1s - loss: 0.1811 - categorical_accuracy: 0.9408 - val_loss: 0.2175 - val_categorical_accuracy: 0.9272 - 523ms/epoch - 26ms/step
Epoch 1275/1500
20/20 - 1s - loss: 0.1862 - categorical_accuracy: 0.9390 - val_loss: 0.2434 - val_categorical_accuracy: 0.9178 - 505ms/epoch - 25ms/step
Epoch 1276/1500
20/20 - 1s - loss: 0.5963 - categorical_accuracy: 0.8513 - val_loss: 4.0629 - val_categorical_accuracy: 0.6629 - 517ms/epoch - 26ms/step
Epoch 1277/1500
20/20 - 1s - loss: 0.4630 - categorical_accuracy: 0.9054 - val_loss: 0.2299 - val_categorical_accuracy: 0.9225 - 502ms/epoch - 25ms/step
Epoch 1278/1500
20/20 - 0s - loss: 0.1919 - categorical_accuracy: 0.9386 - val_loss: 0.2222 - val_categorical_accuracy: 0.9255 - 488ms/epoch - 24ms/step
Epoch 1279/1500
20/20 - 0s - loss: 0.1853 - categorical_accuracy: 0.9409 - val_loss: 0.2185 - val_categorical_accuracy: 0.9273 - 498ms/epoch - 25ms/step
Epoch 1280/1500
20/20 - 1s - loss: 0.1813 - categorical_accuracy: 0.9423 - val_loss: 0.2135 - val_categorical_accuracy: 0.9291 - 518ms/epoch - 26ms/step
Epoch 1281/1500
20/20 - 0s - loss: 0.1783 - categorical_accuracy: 0.9431 - val_loss: 0.2127 - val_categorical_accuracy: 0.9279 - 490ms/epoch - 25ms/step
Epoch 1282/1500
20/20 - 1s - loss: 0.1773 - categorical_accuracy: 0.9431 - val_loss: 0.2104 - val_categorical_accuracy: 0.9291 - 521ms/epoch - 26ms/step
Epoch 1283/1500
20/20 - 0s - loss: 0.1814 - categorical_accuracy: 0.9402 - val_loss: 0.2550 - val_categorical_accuracy: 0.9069 - 485ms/epoch - 24ms/step
Epoch 1284/1500
20/20 - 1s - loss: 0.2779 - categorical_accuracy: 0.8950 - val_loss: 0.2536 - val_categorical_accuracy: 0.9081 - 503ms/epoch - 25ms/step
Epoch 1285/1500
20/20 - 1s - loss: 0.1821 - categorical_accuracy: 0.9403 - val_loss: 0.2079 - val_categorical_accuracy: 0.9308 - 508ms/epoch - 25ms/step
Epoch 1286/1500
20/20 - 1s - loss: 0.1803 - categorical_accuracy: 0.9417 - val_loss: 0.2277 - val_categorical_accuracy: 0.9220 - 506ms/epoch - 25ms/step
Epoch 1287/1500
20/20 - 0s - loss: 0.2605 - categorical_accuracy: 0.9064 - val_loss: 0.2697 - val_categorical_accuracy: 0.9047 - 493ms/epoch - 25ms/step
Epoch 1288/1500
20/20 - 0s - loss: 0.1897 - categorical_accuracy: 0.9370 - val_loss: 0.2088 - val_categorical_accuracy: 0.9298 - 498ms/epoch - 25ms/step
Epoch 1289/1500
20/20 - 1s - loss: 0.1885 - categorical_accuracy: 0.9372 - val_loss: 0.2843 - val_categorical_accuracy: 0.8910 - 502ms/epoch - 25ms/step
Epoch 1290/1500
20/20 - 1s - loss: 0.2541 - categorical_accuracy: 0.9050 - val_loss: 0.2222 - val_categorical_accuracy: 0.9240 - 513ms/epoch - 26ms/step
Epoch 1291/1500
20/20 - 1s - loss: 0.1783 - categorical_accuracy: 0.9422 - val_loss: 0.2292 - val_categorical_accuracy: 0.9204 - 501ms/epoch - 25ms/step
Epoch 1292/1500
20/20 - 0s - loss: 0.2102 - categorical_accuracy: 0.9264 - val_loss: 0.2955 - val_categorical_accuracy: 0.8920 - 495ms/epoch - 25ms/step
Epoch 1293/1500
20/20 - 1s - loss: 0.2413 - categorical_accuracy: 0.9134 - val_loss: 0.2110 - val_categorical_accuracy: 0.9293 - 530ms/epoch - 27ms/step
Epoch 1294/1500
20/20 - 1s - loss: 0.1788 - categorical_accuracy: 0.9411 - val_loss: 0.2303 - val_categorical_accuracy: 0.9199 - 505ms/epoch - 25ms/step
Epoch 1295/1500
20/20 - 0s - loss: 0.2229 - categorical_accuracy: 0.9197 - val_loss: 0.2696 - val_categorical_accuracy: 0.9042 - 481ms/epoch - 24ms/step
Epoch 1296/1500
20/20 - 0s - loss: 0.2059 - categorical_accuracy: 0.9267 - val_loss: 0.2488 - val_categorical_accuracy: 0.9124 - 484ms/epoch - 24ms/step
Epoch 1297/1500
20/20 - 0s - loss: 0.1929 - categorical_accuracy: 0.9340 - val_loss: 0.2131 - val_categorical_accuracy: 0.9267 - 469ms/epoch - 23ms/step
Epoch 1298/1500
20/20 - 0s - loss: 0.1964 - categorical_accuracy: 0.9325 - val_loss: 0.2795 - val_categorical_accuracy: 0.9002 - 481ms/epoch - 24ms/step
Epoch 1299/1500
20/20 - 0s - loss: 0.2229 - categorical_accuracy: 0.9201 - val_loss: 0.2190 - val_categorical_accuracy: 0.9246 - 468ms/epoch - 23ms/step
Epoch 1300/1500
20/20 - 0s - loss: 0.1848 - categorical_accuracy: 0.9379 - val_loss: 0.2168 - val_categorical_accuracy: 0.9258 - 473ms/epoch - 24ms/step
Epoch 1301/1500
20/20 - 0s - loss: 0.1895 - categorical_accuracy: 0.9354 - val_loss: 0.2492 - val_categorical_accuracy: 0.9099 - 486ms/epoch - 24ms/step
Epoch 1302/1500
20/20 - 0s - loss: 0.2428 - categorical_accuracy: 0.9096 - val_loss: 0.2431 - val_categorical_accuracy: 0.9131 - 485ms/epoch - 24ms/step
Epoch 1303/1500
20/20 - 1s - loss: 0.1835 - categorical_accuracy: 0.9384 - val_loss: 0.2112 - val_categorical_accuracy: 0.9292 - 504ms/epoch - 25ms/step
Epoch 1304/1500
20/20 - 0s - loss: 0.1919 - categorical_accuracy: 0.9348 - val_loss: 0.2919 - val_categorical_accuracy: 0.8915 - 471ms/epoch - 24ms/step
Epoch 1305/1500
20/20 - 0s - loss: 0.2546 - categorical_accuracy: 0.9072 - val_loss: 0.2321 - val_categorical_accuracy: 0.9208 - 468ms/epoch - 23ms/step
Epoch 1306/1500
20/20 - 0s - loss: 0.1847 - categorical_accuracy: 0.9387 - val_loss: 0.2138 - val_categorical_accuracy: 0.9282 - 467ms/epoch - 23ms/step
Epoch 1307/1500
20/20 - 0s - loss: 0.1953 - categorical_accuracy: 0.9336 - val_loss: 0.2484 - val_categorical_accuracy: 0.9127 - 473ms/epoch - 24ms/step
Epoch 1308/1500
20/20 - 0s - loss: 0.1977 - categorical_accuracy: 0.9315 - val_loss: 0.2364 - val_categorical_accuracy: 0.9159 - 473ms/epoch - 24ms/step
Epoch 1309/1500
20/20 - 0s - loss: 0.2979 - categorical_accuracy: 0.8905 - val_loss: 1.0101 - val_categorical_accuracy: 0.7254 - 462ms/epoch - 23ms/step
Epoch 1310/1500
20/20 - 0s - loss: 0.3242 - categorical_accuracy: 0.9189 - val_loss: 0.2119 - val_categorical_accuracy: 0.9293 - 471ms/epoch - 24ms/step
Epoch 1311/1500
20/20 - 0s - loss: 0.1750 - categorical_accuracy: 0.9436 - val_loss: 0.2079 - val_categorical_accuracy: 0.9308 - 480ms/epoch - 24ms/step
Epoch 1312/1500
20/20 - 0s - loss: 0.1719 - categorical_accuracy: 0.9448 - val_loss: 0.2082 - val_categorical_accuracy: 0.9301 - 470ms/epoch - 24ms/step
Epoch 1313/1500
20/20 - 0s - loss: 0.1800 - categorical_accuracy: 0.9405 - val_loss: 0.2362 - val_categorical_accuracy: 0.9174 - 474ms/epoch - 24ms/step
Epoch 1314/1500
20/20 - 0s - loss: 0.2489 - categorical_accuracy: 0.9091 - val_loss: 0.3829 - val_categorical_accuracy: 0.8646 - 466ms/epoch - 23ms/step
Epoch 1315/1500
20/20 - 0s - loss: 0.2046 - categorical_accuracy: 0.9297 - val_loss: 0.2059 - val_categorical_accuracy: 0.9318 - 473ms/epoch - 24ms/step
Epoch 1316/1500
20/20 - 0s - loss: 0.1772 - categorical_accuracy: 0.9422 - val_loss: 0.2367 - val_categorical_accuracy: 0.9171 - 469ms/epoch - 23ms/step
Epoch 1317/1500
20/20 - 0s - loss: 0.2063 - categorical_accuracy: 0.9268 - val_loss: 0.2625 - val_categorical_accuracy: 0.9027 - 466ms/epoch - 23ms/step
Epoch 1318/1500
20/20 - 0s - loss: 0.2420 - categorical_accuracy: 0.9107 - val_loss: 0.2176 - val_categorical_accuracy: 0.9251 - 496ms/epoch - 25ms/step
Epoch 1319/1500
20/20 - 0s - loss: 0.1739 - categorical_accuracy: 0.9430 - val_loss: 0.2214 - val_categorical_accuracy: 0.9234 - 480ms/epoch - 24ms/step
Epoch 1320/1500
20/20 - 0s - loss: 0.1973 - categorical_accuracy: 0.9317 - val_loss: 0.2417 - val_categorical_accuracy: 0.9145 - 486ms/epoch - 24ms/step
Epoch 1321/1500
20/20 - 0s - loss: 0.1879 - categorical_accuracy: 0.9367 - val_loss: 0.2221 - val_categorical_accuracy: 0.9223 - 471ms/epoch - 24ms/step
Epoch 1322/1500
20/20 - 0s - loss: 0.2065 - categorical_accuracy: 0.9283 - val_loss: 0.2326 - val_categorical_accuracy: 0.9182 - 472ms/epoch - 24ms/step
Epoch 1323/1500
20/20 - 0s - loss: 0.1870 - categorical_accuracy: 0.9368 - val_loss: 0.2144 - val_categorical_accuracy: 0.9259 - 490ms/epoch - 25ms/step
Epoch 1324/1500
20/20 - 0s - loss: 0.1752 - categorical_accuracy: 0.9424 - val_loss: 0.2438 - val_categorical_accuracy: 0.9134 - 472ms/epoch - 24ms/step
Epoch 1325/1500
20/20 - 0s - loss: 0.2031 - categorical_accuracy: 0.9291 - val_loss: 0.2481 - val_categorical_accuracy: 0.9124 - 484ms/epoch - 24ms/step
Epoch 1326/1500
20/20 - 0s - loss: 0.2770 - categorical_accuracy: 0.8954 - val_loss: 0.2913 - val_categorical_accuracy: 0.8948 - 484ms/epoch - 24ms/step
Epoch 1327/1500
20/20 - 0s - loss: 0.1960 - categorical_accuracy: 0.9322 - val_loss: 0.2121 - val_categorical_accuracy: 0.9268 - 472ms/epoch - 24ms/step
Epoch 1328/1500
20/20 - 0s - loss: 0.1735 - categorical_accuracy: 0.9434 - val_loss: 0.2463 - val_categorical_accuracy: 0.9128 - 474ms/epoch - 24ms/step
Epoch 1329/1500
20/20 - 0s - loss: 0.2278 - categorical_accuracy: 0.9181 - val_loss: 0.2625 - val_categorical_accuracy: 0.9066 - 466ms/epoch - 23ms/step
Epoch 1330/1500
20/20 - 0s - loss: 0.1814 - categorical_accuracy: 0.9394 - val_loss: 0.2065 - val_categorical_accuracy: 0.9295 - 480ms/epoch - 24ms/step
Epoch 1331/1500
20/20 - 0s - loss: 0.1701 - categorical_accuracy: 0.9447 - val_loss: 0.2083 - val_categorical_accuracy: 0.9298 - 490ms/epoch - 25ms/step
Epoch 1332/1500
20/20 - 0s - loss: 0.2383 - categorical_accuracy: 0.9132 - val_loss: 0.2997 - val_categorical_accuracy: 0.8871 - 486ms/epoch - 24ms/step
Epoch 1333/1500
20/20 - 0s - loss: 0.2016 - categorical_accuracy: 0.9288 - val_loss: 0.2074 - val_categorical_accuracy: 0.9306 - 491ms/epoch - 25ms/step
Epoch 1334/1500
20/20 - 0s - loss: 0.1853 - categorical_accuracy: 0.9384 - val_loss: 0.2295 - val_categorical_accuracy: 0.9203 - 480ms/epoch - 24ms/step
Epoch 1335/1500
20/20 - 0s - loss: 0.2538 - categorical_accuracy: 0.9073 - val_loss: 0.2672 - val_categorical_accuracy: 0.9060 - 490ms/epoch - 25ms/step
Epoch 1336/1500
20/20 - 0s - loss: 0.1854 - categorical_accuracy: 0.9377 - val_loss: 0.2059 - val_categorical_accuracy: 0.9304 - 475ms/epoch - 24ms/step
Epoch 1337/1500
20/20 - 0s - loss: 0.1743 - categorical_accuracy: 0.9426 - val_loss: 0.2106 - val_categorical_accuracy: 0.9279 - 479ms/epoch - 24ms/step
Epoch 1338/1500
20/20 - 0s - loss: 0.2207 - categorical_accuracy: 0.9201 - val_loss: 0.3317 - val_categorical_accuracy: 0.8802 - 491ms/epoch - 25ms/step
Epoch 1339/1500
20/20 - 0s - loss: 0.5428 - categorical_accuracy: 0.8585 - val_loss: 0.2201 - val_categorical_accuracy: 0.9271 - 490ms/epoch - 25ms/step
Epoch 1340/1500
20/20 - 0s - loss: 0.1774 - categorical_accuracy: 0.9432 - val_loss: 0.2091 - val_categorical_accuracy: 0.9311 - 490ms/epoch - 25ms/step
Epoch 1341/1500
20/20 - 0s - loss: 0.1706 - categorical_accuracy: 0.9455 - val_loss: 0.2047 - val_categorical_accuracy: 0.9322 - 488ms/epoch - 24ms/step
Epoch 1342/1500
20/20 - 0s - loss: 0.1691 - categorical_accuracy: 0.9457 - val_loss: 0.2031 - val_categorical_accuracy: 0.9326 - 482ms/epoch - 24ms/step
Epoch 1343/1500
20/20 - 0s - loss: 0.1710 - categorical_accuracy: 0.9449 - val_loss: 0.2126 - val_categorical_accuracy: 0.9275 - 487ms/epoch - 24ms/step
Epoch 1344/1500
20/20 - 0s - loss: 0.1785 - categorical_accuracy: 0.9401 - val_loss: 0.2284 - val_categorical_accuracy: 0.9206 - 480ms/epoch - 24ms/step
Epoch 1345/1500
20/20 - 0s - loss: 0.2109 - categorical_accuracy: 0.9251 - val_loss: 0.2710 - val_categorical_accuracy: 0.9020 - 476ms/epoch - 24ms/step
Epoch 1346/1500
20/20 - 0s - loss: 0.2346 - categorical_accuracy: 0.9150 - val_loss: 0.2552 - val_categorical_accuracy: 0.9102 - 493ms/epoch - 25ms/step
Epoch 1347/1500
20/20 - 1s - loss: 0.1836 - categorical_accuracy: 0.9385 - val_loss: 0.2143 - val_categorical_accuracy: 0.9279 - 500ms/epoch - 25ms/step
Epoch 1348/1500
20/20 - 0s - loss: 0.1866 - categorical_accuracy: 0.9368 - val_loss: 0.2279 - val_categorical_accuracy: 0.9198 - 472ms/epoch - 24ms/step
Epoch 1349/1500
20/20 - 0s - loss: 0.1968 - categorical_accuracy: 0.9310 - val_loss: 0.2400 - val_categorical_accuracy: 0.9152 - 478ms/epoch - 24ms/step
Epoch 1350/1500
20/20 - 0s - loss: 0.2001 - categorical_accuracy: 0.9292 - val_loss: 0.2033 - val_categorical_accuracy: 0.9314 - 478ms/epoch - 24ms/step
Epoch 1351/1500
20/20 - 0s - loss: 0.1736 - categorical_accuracy: 0.9436 - val_loss: 0.2570 - val_categorical_accuracy: 0.9085 - 486ms/epoch - 24ms/step
Epoch 1352/1500
20/20 - 0s - loss: 0.2856 - categorical_accuracy: 0.8964 - val_loss: 0.2132 - val_categorical_accuracy: 0.9269 - 483ms/epoch - 24ms/step
Epoch 1353/1500
20/20 - 0s - loss: 0.1659 - categorical_accuracy: 0.9467 - val_loss: 0.2011 - val_categorical_accuracy: 0.9331 - 487ms/epoch - 24ms/step
Epoch 1354/1500
20/20 - 0s - loss: 0.1693 - categorical_accuracy: 0.9447 - val_loss: 0.2187 - val_categorical_accuracy: 0.9250 - 484ms/epoch - 24ms/step
Epoch 1355/1500
20/20 - 0s - loss: 0.1978 - categorical_accuracy: 0.9310 - val_loss: 0.2357 - val_categorical_accuracy: 0.9152 - 473ms/epoch - 24ms/step
Epoch 1356/1500
20/20 - 0s - loss: 0.2097 - categorical_accuracy: 0.9239 - val_loss: 0.2294 - val_categorical_accuracy: 0.9202 - 474ms/epoch - 24ms/step
Epoch 1357/1500
20/20 - 0s - loss: 0.1986 - categorical_accuracy: 0.9309 - val_loss: 0.2201 - val_categorical_accuracy: 0.9232 - 496ms/epoch - 25ms/step
Epoch 1358/1500
20/20 - 0s - loss: 0.1899 - categorical_accuracy: 0.9352 - val_loss: 0.2276 - val_categorical_accuracy: 0.9195 - 498ms/epoch - 25ms/step
Epoch 1359/1500
20/20 - 1s - loss: 0.1937 - categorical_accuracy: 0.9323 - val_loss: 0.2261 - val_categorical_accuracy: 0.9225 - 504ms/epoch - 25ms/step
Epoch 1360/1500
20/20 - 1s - loss: 0.2032 - categorical_accuracy: 0.9285 - val_loss: 0.2882 - val_categorical_accuracy: 0.8953 - 503ms/epoch - 25ms/step
Epoch 1361/1500
20/20 - 1s - loss: 0.2067 - categorical_accuracy: 0.9273 - val_loss: 0.2067 - val_categorical_accuracy: 0.9308 - 524ms/epoch - 26ms/step
Epoch 1362/1500
20/20 - 1s - loss: 0.1637 - categorical_accuracy: 0.9476 - val_loss: 0.2071 - val_categorical_accuracy: 0.9285 - 512ms/epoch - 26ms/step
Epoch 1363/1500
20/20 - 0s - loss: 0.1878 - categorical_accuracy: 0.9362 - val_loss: 0.2780 - val_categorical_accuracy: 0.9011 - 494ms/epoch - 25ms/step
Epoch 1364/1500
20/20 - 0s - loss: 0.2499 - categorical_accuracy: 0.9088 - val_loss: 0.2367 - val_categorical_accuracy: 0.9162 - 496ms/epoch - 25ms/step
Epoch 1365/1500
20/20 - 0s - loss: 0.1970 - categorical_accuracy: 0.9313 - val_loss: 0.2235 - val_categorical_accuracy: 0.9221 - 483ms/epoch - 24ms/step
Epoch 1366/1500
20/20 - 0s - loss: 0.1803 - categorical_accuracy: 0.9392 - val_loss: 0.2130 - val_categorical_accuracy: 0.9280 - 486ms/epoch - 24ms/step
Epoch 1367/1500
20/20 - 1s - loss: 0.1954 - categorical_accuracy: 0.9317 - val_loss: 0.2408 - val_categorical_accuracy: 0.9125 - 503ms/epoch - 25ms/step
Epoch 1368/1500
20/20 - 1s - loss: 0.1895 - categorical_accuracy: 0.9347 - val_loss: 0.2158 - val_categorical_accuracy: 0.9261 - 505ms/epoch - 25ms/step
Epoch 1369/1500
20/20 - 0s - loss: 0.1741 - categorical_accuracy: 0.9421 - val_loss: 0.2270 - val_categorical_accuracy: 0.9207 - 482ms/epoch - 24ms/step
Epoch 1370/1500
20/20 - 1s - loss: 0.2079 - categorical_accuracy: 0.9266 - val_loss: 0.2299 - val_categorical_accuracy: 0.9207 - 505ms/epoch - 25ms/step
Epoch 1371/1500
20/20 - 0s - loss: 0.1842 - categorical_accuracy: 0.9377 - val_loss: 0.2069 - val_categorical_accuracy: 0.9307 - 489ms/epoch - 24ms/step
Epoch 1372/1500
20/20 - 0s - loss: 0.1719 - categorical_accuracy: 0.9440 - val_loss: 0.2067 - val_categorical_accuracy: 0.9301 - 490ms/epoch - 25ms/step
Epoch 1373/1500
20/20 - 0s - loss: 0.2092 - categorical_accuracy: 0.9282 - val_loss: 0.8781 - val_categorical_accuracy: 0.7598 - 484ms/epoch - 24ms/step
Epoch 1374/1500
20/20 - 0s - loss: 0.3524 - categorical_accuracy: 0.9147 - val_loss: 0.2015 - val_categorical_accuracy: 0.9318 - 497ms/epoch - 25ms/step
Epoch 1375/1500
20/20 - 1s - loss: 0.1629 - categorical_accuracy: 0.9475 - val_loss: 0.2014 - val_categorical_accuracy: 0.9313 - 500ms/epoch - 25ms/step
Epoch 1376/1500
20/20 - 1s - loss: 0.1643 - categorical_accuracy: 0.9467 - val_loss: 0.1970 - val_categorical_accuracy: 0.9342 - 504ms/epoch - 25ms/step
Epoch 1377/1500
20/20 - 0s - loss: 0.1680 - categorical_accuracy: 0.9450 - val_loss: 0.2342 - val_categorical_accuracy: 0.9187 - 498ms/epoch - 25ms/step
Epoch 1378/1500
20/20 - 0s - loss: 0.4541 - categorical_accuracy: 0.8639 - val_loss: 0.2298 - val_categorical_accuracy: 0.9215 - 490ms/epoch - 25ms/step
Epoch 1379/1500
20/20 - 0s - loss: 0.1703 - categorical_accuracy: 0.9446 - val_loss: 0.2017 - val_categorical_accuracy: 0.9324 - 493ms/epoch - 25ms/step
Epoch 1380/1500
20/20 - 0s - loss: 0.1655 - categorical_accuracy: 0.9468 - val_loss: 0.2091 - val_categorical_accuracy: 0.9290 - 499ms/epoch - 25ms/step
Epoch 1381/1500
20/20 - 0s - loss: 0.1873 - categorical_accuracy: 0.9357 - val_loss: 0.2356 - val_categorical_accuracy: 0.9171 - 464ms/epoch - 23ms/step
Epoch 1382/1500
20/20 - 0s - loss: 0.1872 - categorical_accuracy: 0.9353 - val_loss: 0.2082 - val_categorical_accuracy: 0.9288 - 461ms/epoch - 23ms/step
Epoch 1383/1500
20/20 - 0s - loss: 0.1740 - categorical_accuracy: 0.9417 - val_loss: 0.2720 - val_categorical_accuracy: 0.9053 - 458ms/epoch - 23ms/step
Epoch 1384/1500
20/20 - 0s - loss: 0.2114 - categorical_accuracy: 0.9243 - val_loss: 0.2461 - val_categorical_accuracy: 0.9132 - 454ms/epoch - 23ms/step
Epoch 1385/1500
20/20 - 0s - loss: 0.1907 - categorical_accuracy: 0.9338 - val_loss: 0.2331 - val_categorical_accuracy: 0.9179 - 463ms/epoch - 23ms/step
Epoch 1386/1500
20/20 - 0s - loss: 0.1909 - categorical_accuracy: 0.9339 - val_loss: 0.2186 - val_categorical_accuracy: 0.9238 - 456ms/epoch - 23ms/step
Epoch 1387/1500
20/20 - 0s - loss: 0.1736 - categorical_accuracy: 0.9413 - val_loss: 0.2064 - val_categorical_accuracy: 0.9287 - 456ms/epoch - 23ms/step
Epoch 1388/1500
20/20 - 0s - loss: 0.1669 - categorical_accuracy: 0.9457 - val_loss: 0.2328 - val_categorical_accuracy: 0.9183 - 457ms/epoch - 23ms/step
Epoch 1389/1500
20/20 - 0s - loss: 0.2727 - categorical_accuracy: 0.9004 - val_loss: 0.3524 - val_categorical_accuracy: 0.8734 - 467ms/epoch - 23ms/step
Epoch 1390/1500
20/20 - 0s - loss: 0.2139 - categorical_accuracy: 0.9243 - val_loss: 0.2214 - val_categorical_accuracy: 0.9232 - 457ms/epoch - 23ms/step
Epoch 1391/1500
20/20 - 0s - loss: 0.1749 - categorical_accuracy: 0.9420 - val_loss: 0.2104 - val_categorical_accuracy: 0.9295 - 459ms/epoch - 23ms/step
Epoch 1392/1500
20/20 - 0s - loss: 0.1938 - categorical_accuracy: 0.9320 - val_loss: 0.2308 - val_categorical_accuracy: 0.9196 - 478ms/epoch - 24ms/step
Epoch 1393/1500
20/20 - 0s - loss: 0.1833 - categorical_accuracy: 0.9377 - val_loss: 0.2182 - val_categorical_accuracy: 0.9244 - 488ms/epoch - 24ms/step
Epoch 1394/1500
20/20 - 0s - loss: 0.1781 - categorical_accuracy: 0.9396 - val_loss: 0.2092 - val_categorical_accuracy: 0.9296 - 466ms/epoch - 23ms/step
Epoch 1395/1500
20/20 - 0s - loss: 0.2088 - categorical_accuracy: 0.9252 - val_loss: 0.2193 - val_categorical_accuracy: 0.9240 - 489ms/epoch - 24ms/step
Epoch 1396/1500
20/20 - 0s - loss: 0.1629 - categorical_accuracy: 0.9470 - val_loss: 0.1941 - val_categorical_accuracy: 0.9351 - 488ms/epoch - 24ms/step
Epoch 1397/1500
20/20 - 0s - loss: 0.1728 - categorical_accuracy: 0.9419 - val_loss: 0.2729 - val_categorical_accuracy: 0.8987 - 488ms/epoch - 24ms/step
Epoch 1398/1500
20/20 - 0s - loss: 0.3085 - categorical_accuracy: 0.8871 - val_loss: 0.2153 - val_categorical_accuracy: 0.9257 - 473ms/epoch - 24ms/step
Epoch 1399/1500
20/20 - 0s - loss: 0.1632 - categorical_accuracy: 0.9475 - val_loss: 0.1953 - val_categorical_accuracy: 0.9353 - 481ms/epoch - 24ms/step
Epoch 1400/1500
20/20 - 0s - loss: 0.1591 - categorical_accuracy: 0.9491 - val_loss: 0.1987 - val_categorical_accuracy: 0.9322 - 480ms/epoch - 24ms/step
Epoch 1401/1500
20/20 - 0s - loss: 0.1763 - categorical_accuracy: 0.9407 - val_loss: 0.2693 - val_categorical_accuracy: 0.9045 - 467ms/epoch - 23ms/step
Epoch 1402/1500
20/20 - 0s - loss: 0.1985 - categorical_accuracy: 0.9307 - val_loss: 0.2158 - val_categorical_accuracy: 0.9245 - 474ms/epoch - 24ms/step
Epoch 1403/1500
20/20 - 0s - loss: 0.1757 - categorical_accuracy: 0.9411 - val_loss: 0.2176 - val_categorical_accuracy: 0.9241 - 483ms/epoch - 24ms/step
Epoch 1404/1500
20/20 - 0s - loss: 0.1913 - categorical_accuracy: 0.9335 - val_loss: 0.2620 - val_categorical_accuracy: 0.9070 - 476ms/epoch - 24ms/step
Epoch 1405/1500
20/20 - 0s - loss: 0.2306 - categorical_accuracy: 0.9154 - val_loss: 0.2765 - val_categorical_accuracy: 0.9018 - 473ms/epoch - 24ms/step
Epoch 1406/1500
20/20 - 0s - loss: 0.2095 - categorical_accuracy: 0.9249 - val_loss: 0.2367 - val_categorical_accuracy: 0.9186 - 472ms/epoch - 24ms/step
Epoch 1407/1500
20/20 - 0s - loss: 0.1680 - categorical_accuracy: 0.9451 - val_loss: 0.2009 - val_categorical_accuracy: 0.9319 - 480ms/epoch - 24ms/step
Epoch 1408/1500
20/20 - 0s - loss: 0.1771 - categorical_accuracy: 0.9402 - val_loss: 0.2353 - val_categorical_accuracy: 0.9173 - 466ms/epoch - 23ms/step
Epoch 1409/1500
20/20 - 0s - loss: 0.1916 - categorical_accuracy: 0.9331 - val_loss: 0.2266 - val_categorical_accuracy: 0.9201 - 478ms/epoch - 24ms/step
Epoch 1410/1500
20/20 - 0s - loss: 0.1847 - categorical_accuracy: 0.9363 - val_loss: 0.2226 - val_categorical_accuracy: 0.9224 - 478ms/epoch - 24ms/step
Epoch 1411/1500
20/20 - 0s - loss: 0.1707 - categorical_accuracy: 0.9429 - val_loss: 0.2166 - val_categorical_accuracy: 0.9244 - 462ms/epoch - 23ms/step
Epoch 1412/1500
20/20 - 0s - loss: 0.1986 - categorical_accuracy: 0.9290 - val_loss: 0.2718 - val_categorical_accuracy: 0.9031 - 456ms/epoch - 23ms/step
Epoch 1413/1500
20/20 - 0s - loss: 0.4169 - categorical_accuracy: 0.8744 - val_loss: 0.2056 - val_categorical_accuracy: 0.9310 - 453ms/epoch - 23ms/step
Epoch 1414/1500
20/20 - 0s - loss: 0.1637 - categorical_accuracy: 0.9471 - val_loss: 0.2005 - val_categorical_accuracy: 0.9333 - 444ms/epoch - 22ms/step
Epoch 1415/1500
20/20 - 0s - loss: 0.1592 - categorical_accuracy: 0.9490 - val_loss: 0.1946 - val_categorical_accuracy: 0.9349 - 460ms/epoch - 23ms/step
Epoch 1416/1500
20/20 - 0s - loss: 0.1567 - categorical_accuracy: 0.9502 - val_loss: 0.1937 - val_categorical_accuracy: 0.9357 - 473ms/epoch - 24ms/step
Epoch 1417/1500
20/20 - 0s - loss: 0.1562 - categorical_accuracy: 0.9501 - val_loss: 0.1992 - val_categorical_accuracy: 0.9342 - 475ms/epoch - 24ms/step
Epoch 1418/1500
20/20 - 0s - loss: 0.2279 - categorical_accuracy: 0.9185 - val_loss: 0.3481 - val_categorical_accuracy: 0.8749 - 499ms/epoch - 25ms/step
Epoch 1419/1500
20/20 - 0s - loss: 0.2274 - categorical_accuracy: 0.9185 - val_loss: 0.2277 - val_categorical_accuracy: 0.9205 - 478ms/epoch - 24ms/step
Epoch 1420/1500
20/20 - 0s - loss: 0.1847 - categorical_accuracy: 0.9359 - val_loss: 0.1993 - val_categorical_accuracy: 0.9325 - 449ms/epoch - 22ms/step
Epoch 1421/1500
20/20 - 0s - loss: 0.1673 - categorical_accuracy: 0.9446 - val_loss: 0.2154 - val_categorical_accuracy: 0.9249 - 439ms/epoch - 22ms/step
Epoch 1422/1500
20/20 - 0s - loss: 0.1801 - categorical_accuracy: 0.9384 - val_loss: 0.2409 - val_categorical_accuracy: 0.9156 - 427ms/epoch - 21ms/step
Epoch 1423/1500
20/20 - 0s - loss: 0.1775 - categorical_accuracy: 0.9398 - val_loss: 0.2238 - val_categorical_accuracy: 0.9221 - 444ms/epoch - 22ms/step
Epoch 1424/1500
20/20 - 0s - loss: 0.1826 - categorical_accuracy: 0.9381 - val_loss: 0.2075 - val_categorical_accuracy: 0.9278 - 462ms/epoch - 23ms/step
Epoch 1425/1500
20/20 - 0s - loss: 0.1667 - categorical_accuracy: 0.9447 - val_loss: 0.2074 - val_categorical_accuracy: 0.9284 - 466ms/epoch - 23ms/step
Epoch 1426/1500
20/20 - 0s - loss: 0.2675 - categorical_accuracy: 0.9043 - val_loss: 0.9558 - val_categorical_accuracy: 0.7870 - 443ms/epoch - 22ms/step
Epoch 1427/1500
20/20 - 0s - loss: 0.3785 - categorical_accuracy: 0.9107 - val_loss: 0.1990 - val_categorical_accuracy: 0.9334 - 447ms/epoch - 22ms/step
Epoch 1428/1500
20/20 - 0s - loss: 0.1605 - categorical_accuracy: 0.9488 - val_loss: 0.1973 - val_categorical_accuracy: 0.9353 - 441ms/epoch - 22ms/step
Epoch 1429/1500
20/20 - 0s - loss: 0.1607 - categorical_accuracy: 0.9482 - val_loss: 0.2043 - val_categorical_accuracy: 0.9313 - 451ms/epoch - 23ms/step
Epoch 1430/1500
20/20 - 0s - loss: 0.1660 - categorical_accuracy: 0.9456 - val_loss: 0.2006 - val_categorical_accuracy: 0.9332 - 451ms/epoch - 23ms/step
Epoch 1431/1500
20/20 - 0s - loss: 0.1600 - categorical_accuracy: 0.9481 - val_loss: 0.1971 - val_categorical_accuracy: 0.9349 - 454ms/epoch - 23ms/step
Epoch 1432/1500
20/20 - 0s - loss: 0.2005 - categorical_accuracy: 0.9290 - val_loss: 0.2595 - val_categorical_accuracy: 0.9081 - 439ms/epoch - 22ms/step
Epoch 1433/1500
20/20 - 0s - loss: 0.2100 - categorical_accuracy: 0.9256 - val_loss: 0.2025 - val_categorical_accuracy: 0.9319 - 444ms/epoch - 22ms/step
Epoch 1434/1500
20/20 - 0s - loss: 0.1655 - categorical_accuracy: 0.9457 - val_loss: 0.1990 - val_categorical_accuracy: 0.9332 - 440ms/epoch - 22ms/step
Epoch 1435/1500
20/20 - 0s - loss: 0.1668 - categorical_accuracy: 0.9446 - val_loss: 0.2314 - val_categorical_accuracy: 0.9163 - 444ms/epoch - 22ms/step
Epoch 1436/1500
20/20 - 0s - loss: 0.2545 - categorical_accuracy: 0.9049 - val_loss: 0.2629 - val_categorical_accuracy: 0.9036 - 438ms/epoch - 22ms/step
Epoch 1437/1500
20/20 - 0s - loss: 0.1642 - categorical_accuracy: 0.9456 - val_loss: 0.1957 - val_categorical_accuracy: 0.9345 - 451ms/epoch - 23ms/step
Epoch 1438/1500
20/20 - 0s - loss: 0.1712 - categorical_accuracy: 0.9428 - val_loss: 0.2110 - val_categorical_accuracy: 0.9273 - 439ms/epoch - 22ms/step
Epoch 1439/1500
20/20 - 0s - loss: 0.1651 - categorical_accuracy: 0.9452 - val_loss: 0.1923 - val_categorical_accuracy: 0.9363 - 449ms/epoch - 22ms/step
Epoch 1440/1500
20/20 - 0s - loss: 0.1684 - categorical_accuracy: 0.9443 - val_loss: 0.2208 - val_categorical_accuracy: 0.9231 - 446ms/epoch - 22ms/step
Epoch 1441/1500
20/20 - 0s - loss: 0.1985 - categorical_accuracy: 0.9295 - val_loss: 0.2028 - val_categorical_accuracy: 0.9324 - 449ms/epoch - 22ms/step
Epoch 1442/1500
20/20 - 0s - loss: 0.1806 - categorical_accuracy: 0.9380 - val_loss: 0.2456 - val_categorical_accuracy: 0.9135 - 441ms/epoch - 22ms/step
Epoch 1443/1500
20/20 - 0s - loss: 0.2696 - categorical_accuracy: 0.9033 - val_loss: 0.4443 - val_categorical_accuracy: 0.8483 - 442ms/epoch - 22ms/step
Epoch 1444/1500
20/20 - 0s - loss: 0.2110 - categorical_accuracy: 0.9263 - val_loss: 0.1972 - val_categorical_accuracy: 0.9327 - 444ms/epoch - 22ms/step
Epoch 1445/1500
20/20 - 0s - loss: 0.1546 - categorical_accuracy: 0.9507 - val_loss: 0.1928 - val_categorical_accuracy: 0.9353 - 423ms/epoch - 21ms/step
Epoch 1446/1500
20/20 - 0s - loss: 0.1722 - categorical_accuracy: 0.9423 - val_loss: 0.2253 - val_categorical_accuracy: 0.9230 - 432ms/epoch - 22ms/step
Epoch 1447/1500
20/20 - 0s - loss: 0.1695 - categorical_accuracy: 0.9433 - val_loss: 0.2135 - val_categorical_accuracy: 0.9264 - 438ms/epoch - 22ms/step
Epoch 1448/1500
20/20 - 0s - loss: 0.1672 - categorical_accuracy: 0.9442 - val_loss: 0.2040 - val_categorical_accuracy: 0.9316 - 440ms/epoch - 22ms/step
Epoch 1449/1500
20/20 - 0s - loss: 0.1685 - categorical_accuracy: 0.9439 - val_loss: 0.2251 - val_categorical_accuracy: 0.9217 - 445ms/epoch - 22ms/step
Epoch 1450/1500
20/20 - 0s - loss: 0.1833 - categorical_accuracy: 0.9370 - val_loss: 0.2132 - val_categorical_accuracy: 0.9265 - 430ms/epoch - 22ms/step
Epoch 1451/1500
20/20 - 0s - loss: 0.1735 - categorical_accuracy: 0.9412 - val_loss: 0.2059 - val_categorical_accuracy: 0.9306 - 448ms/epoch - 22ms/step
Epoch 1452/1500
20/20 - 0s - loss: 0.2371 - categorical_accuracy: 0.9134 - val_loss: 0.4076 - val_categorical_accuracy: 0.8577 - 441ms/epoch - 22ms/step
Epoch 1453/1500
20/20 - 0s - loss: 0.2147 - categorical_accuracy: 0.9241 - val_loss: 0.1918 - val_categorical_accuracy: 0.9353 - 450ms/epoch - 23ms/step
Epoch 1454/1500
20/20 - 0s - loss: 0.1563 - categorical_accuracy: 0.9492 - val_loss: 0.2030 - val_categorical_accuracy: 0.9298 - 442ms/epoch - 22ms/step
Epoch 1455/1500
20/20 - 0s - loss: 0.1666 - categorical_accuracy: 0.9444 - val_loss: 0.2228 - val_categorical_accuracy: 0.9223 - 427ms/epoch - 21ms/step
Epoch 1456/1500
20/20 - 0s - loss: 0.2046 - categorical_accuracy: 0.9277 - val_loss: 0.2269 - val_categorical_accuracy: 0.9204 - 424ms/epoch - 21ms/step
Epoch 1457/1500
20/20 - 0s - loss: 0.1924 - categorical_accuracy: 0.9328 - val_loss: 0.1924 - val_categorical_accuracy: 0.9351 - 436ms/epoch - 22ms/step
Epoch 1458/1500
20/20 - 0s - loss: 0.1540 - categorical_accuracy: 0.9507 - val_loss: 0.2093 - val_categorical_accuracy: 0.9307 - 443ms/epoch - 22ms/step
Epoch 1459/1500
20/20 - 0s - loss: 0.1627 - categorical_accuracy: 0.9467 - val_loss: 0.1956 - val_categorical_accuracy: 0.9345 - 412ms/epoch - 21ms/step
Epoch 1460/1500
20/20 - 0s - loss: 0.1585 - categorical_accuracy: 0.9484 - val_loss: 0.2121 - val_categorical_accuracy: 0.9279 - 419ms/epoch - 21ms/step
Epoch 1461/1500
20/20 - 0s - loss: 0.2577 - categorical_accuracy: 0.9081 - val_loss: 0.4443 - val_categorical_accuracy: 0.8521 - 418ms/epoch - 21ms/step
Epoch 1462/1500
20/20 - 0s - loss: 0.2136 - categorical_accuracy: 0.9254 - val_loss: 0.1897 - val_categorical_accuracy: 0.9359 - 428ms/epoch - 21ms/step
Epoch 1463/1500
20/20 - 0s - loss: 0.1506 - categorical_accuracy: 0.9522 - val_loss: 0.1892 - val_categorical_accuracy: 0.9366 - 424ms/epoch - 21ms/step
Epoch 1464/1500
20/20 - 0s - loss: 0.1496 - categorical_accuracy: 0.9525 - val_loss: 0.1911 - val_categorical_accuracy: 0.9348 - 415ms/epoch - 21ms/step
Epoch 1465/1500
20/20 - 0s - loss: 0.1783 - categorical_accuracy: 0.9383 - val_loss: 0.3189 - val_categorical_accuracy: 0.8847 - 414ms/epoch - 21ms/step
Epoch 1466/1500
20/20 - 0s - loss: 0.2548 - categorical_accuracy: 0.9116 - val_loss: 0.1932 - val_categorical_accuracy: 0.9346 - 411ms/epoch - 21ms/step
Epoch 1467/1500
20/20 - 0s - loss: 0.1509 - categorical_accuracy: 0.9520 - val_loss: 0.1978 - val_categorical_accuracy: 0.9327 - 427ms/epoch - 21ms/step
Epoch 1468/1500
20/20 - 0s - loss: 0.5248 - categorical_accuracy: 0.8781 - val_loss: 2.5692 - val_categorical_accuracy: 0.6254 - 414ms/epoch - 21ms/step
Epoch 1469/1500
20/20 - 0s - loss: 0.5812 - categorical_accuracy: 0.8863 - val_loss: 0.2152 - val_categorical_accuracy: 0.9279 - 412ms/epoch - 21ms/step
Epoch 1470/1500
20/20 - 0s - loss: 0.1743 - categorical_accuracy: 0.9448 - val_loss: 0.2074 - val_categorical_accuracy: 0.9313 - 412ms/epoch - 21ms/step
Epoch 1471/1500
20/20 - 0s - loss: 0.1667 - categorical_accuracy: 0.9471 - val_loss: 0.2003 - val_categorical_accuracy: 0.9334 - 413ms/epoch - 21ms/step
Epoch 1472/1500
20/20 - 0s - loss: 0.1609 - categorical_accuracy: 0.9491 - val_loss: 0.1954 - val_categorical_accuracy: 0.9353 - 427ms/epoch - 21ms/step
Epoch 1473/1500
20/20 - 0s - loss: 0.1576 - categorical_accuracy: 0.9500 - val_loss: 0.1948 - val_categorical_accuracy: 0.9347 - 418ms/epoch - 21ms/step
Epoch 1474/1500
20/20 - 0s - loss: 0.1549 - categorical_accuracy: 0.9509 - val_loss: 0.1937 - val_categorical_accuracy: 0.9359 - 428ms/epoch - 21ms/step
Epoch 1475/1500
20/20 - 0s - loss: 0.1536 - categorical_accuracy: 0.9513 - val_loss: 0.1937 - val_categorical_accuracy: 0.9355 - 414ms/epoch - 21ms/step
Epoch 1476/1500
20/20 - 0s - loss: 0.1708 - categorical_accuracy: 0.9427 - val_loss: 0.2135 - val_categorical_accuracy: 0.9259 - 415ms/epoch - 21ms/step
Epoch 1477/1500
20/20 - 0s - loss: 0.1783 - categorical_accuracy: 0.9386 - val_loss: 0.2289 - val_categorical_accuracy: 0.9205 - 420ms/epoch - 21ms/step
Epoch 1478/1500
20/20 - 0s - loss: 0.1649 - categorical_accuracy: 0.9458 - val_loss: 0.1928 - val_categorical_accuracy: 0.9365 - 414ms/epoch - 21ms/step
Epoch 1479/1500
20/20 - 0s - loss: 0.1546 - categorical_accuracy: 0.9501 - val_loss: 0.1989 - val_categorical_accuracy: 0.9325 - 429ms/epoch - 21ms/step
Epoch 1480/1500
20/20 - 0s - loss: 0.1907 - categorical_accuracy: 0.9330 - val_loss: 0.2294 - val_categorical_accuracy: 0.9171 - 414ms/epoch - 21ms/step
Epoch 1481/1500
20/20 - 0s - loss: 0.1800 - categorical_accuracy: 0.9370 - val_loss: 0.2177 - val_categorical_accuracy: 0.9246 - 430ms/epoch - 21ms/step
Epoch 1482/1500
20/20 - 0s - loss: 0.1741 - categorical_accuracy: 0.9404 - val_loss: 0.2134 - val_categorical_accuracy: 0.9259 - 421ms/epoch - 21ms/step
Epoch 1483/1500
20/20 - 0s - loss: 0.1771 - categorical_accuracy: 0.9387 - val_loss: 0.2144 - val_categorical_accuracy: 0.9252 - 428ms/epoch - 21ms/step
Epoch 1484/1500
20/20 - 0s - loss: 0.1691 - categorical_accuracy: 0.9430 - val_loss: 0.2095 - val_categorical_accuracy: 0.9280 - 428ms/epoch - 21ms/step
Epoch 1485/1500
20/20 - 0s - loss: 0.1784 - categorical_accuracy: 0.9386 - val_loss: 0.2248 - val_categorical_accuracy: 0.9206 - 412ms/epoch - 21ms/step
Epoch 1486/1500
20/20 - 0s - loss: 0.1795 - categorical_accuracy: 0.9383 - val_loss: 0.3485 - val_categorical_accuracy: 0.8740 - 428ms/epoch - 21ms/step
Epoch 1487/1500
20/20 - 0s - loss: 0.4395 - categorical_accuracy: 0.8546 - val_loss: 1.4707 - val_categorical_accuracy: 0.8042 - 414ms/epoch - 21ms/step
Epoch 1488/1500
20/20 - 0s - loss: 0.2310 - categorical_accuracy: 0.9383 - val_loss: 0.1929 - val_categorical_accuracy: 0.9362 - 427ms/epoch - 21ms/step
Epoch 1489/1500
20/20 - 0s - loss: 0.1540 - categorical_accuracy: 0.9513 - val_loss: 0.1908 - val_categorical_accuracy: 0.9363 - 414ms/epoch - 21ms/step
Epoch 1490/1500
20/20 - 0s - loss: 0.1510 - categorical_accuracy: 0.9520 - val_loss: 0.1884 - val_categorical_accuracy: 0.9365 - 412ms/epoch - 21ms/step
Epoch 1491/1500
20/20 - 0s - loss: 0.1495 - categorical_accuracy: 0.9524 - val_loss: 0.1877 - val_categorical_accuracy: 0.9373 - 422ms/epoch - 21ms/step
Epoch 1492/1500
20/20 - 0s - loss: 0.1590 - categorical_accuracy: 0.9477 - val_loss: 0.2108 - val_categorical_accuracy: 0.9265 - 412ms/epoch - 21ms/step
Epoch 1493/1500
20/20 - 0s - loss: 0.1832 - categorical_accuracy: 0.9361 - val_loss: 0.2195 - val_categorical_accuracy: 0.9229 - 429ms/epoch - 21ms/step
Epoch 1494/1500
20/20 - 0s - loss: 0.2175 - categorical_accuracy: 0.9194 - val_loss: 0.2507 - val_categorical_accuracy: 0.9072 - 441ms/epoch - 22ms/step
Epoch 1495/1500
20/20 - 0s - loss: 0.1699 - categorical_accuracy: 0.9419 - val_loss: 0.1905 - val_categorical_accuracy: 0.9366 - 412ms/epoch - 21ms/step
Epoch 1496/1500
20/20 - 0s - loss: 0.1502 - categorical_accuracy: 0.9517 - val_loss: 0.1914 - val_categorical_accuracy: 0.9354 - 421ms/epoch - 21ms/step
Epoch 1497/1500
20/20 - 0s - loss: 0.1697 - categorical_accuracy: 0.9425 - val_loss: 0.2280 - val_categorical_accuracy: 0.9205 - 415ms/epoch - 21ms/step
Epoch 1498/1500
20/20 - 0s - loss: 0.2008 - categorical_accuracy: 0.9271 - val_loss: 0.2058 - val_categorical_accuracy: 0.9297 - 424ms/epoch - 21ms/step
Epoch 1499/1500
20/20 - 0s - loss: 0.1547 - categorical_accuracy: 0.9499 - val_loss: 0.1885 - val_categorical_accuracy: 0.9384 - 426ms/epoch - 21ms/step
Epoch 1500/1500
20/20 - 0s - loss: 0.1599 - categorical_accuracy: 0.9472 - val_loss: 0.2673 - val_categorical_accuracy: 0.9037 - 413ms/epoch - 21ms/step
#reticulate::py_last_error()

#We can then compute the average of the per-epoch ACC scores for all folds:

head(max(average_acc_history$training_acc))
[1] 0.8260997
head(max(average_acc_history$validation_acc))
[1] 0.9365972
---
title: "Project Part 2"
output:
  html_document:
    df_print: paged
  html_notebook:
    theme: cerulean
    highlight: textmate
  pdf_document: default
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
```

***

This notebook contains the code samples found in Chapter 3, Section 5 of [Deep Learning with R](https://www.manning.com/books/deep-learning-with-r). Note that the original text features far more content, in particular further explanations and figures: in this notebook, you will only find source code and related comments.

***

# Data Exploration & Preparation 
* Our goal in the second part of the assignment is to predict how good a (new) customer will pay 
back their credit card depts. In the data set application data from current customers (the first 18 
attributes) together with their status (last attribute; target) are given.  
* The attributes from the applications are 

Attribute Name | Explanation | Remarks
------------- | ------------- | -------------
ID | Client | number 
CODE_GENDER | Gender | 
FLAG_OWN_CAR | Is there a car | 
FLAG_OWN_REALTY | Is there a property | 
CNT_CHILDREN | Number of children | 
AMT_INCOME_TOTAL | Annual income | 
NAME_INCOME_TYPE | Income category | 
NAME_EDUCATION_TYPE | Education level | 
NAME_FAMILY_STATUS | Marital status | 
NAME_HOUSING_TYPE | Way of living | 
DAYS_BIRTH | Birthday | Count backwards from current day (0), -1 means yesterday 
DAYS_EMPLOYED | Start date of employment | Count backwards from current day(0). If positive, it means the person unemployed. 
FLAG_MOBIL | Is there a mobile phone | 
FLAG_WORK_PHONE | Is there a work phone | 
FLAG_PHONE | Is there a phone | 
FLAG_EMAIL | Is there an email | 
OCCUPATION_TYPE | Occupation | 
CNT_FAM_MEMBERS | Family size | 

* The last attribute status contains the “pay-back behavior”, i.e. when did that customer pay back 
their depts: 
  + 0: 1-29 days past due 
  + 1: 30-59 days past due 
  + 2: 60-89 days overdue 
  + 3: 90-119 days overdue 
  + 4: 120-149 days overdue 
  + 5: Overdue or bad debts, write-offs for more than 150 days 
  + C: paid off that month 
  + X: No loan for the month 
Please note: We are learning only the pay-back behavior. The decision, i.e. if we accept a customer or 
not, is done in another process step – not here!  


***

# Main task 
* Design your network. Why did you use a feed-forward network, or a convolutional or recursive 
network – and why not?  
* Use k-fold validation (with k = 10) to find the best hyperparameters for your network. 
* Use the average of the accuracy to evaluate the performance of your trained network. 
* Find a “reasonable” good model. Argue why that model is reasonable. If you are not able to find a 
reasonable good model, explain what you all did to find a good model and argue why you think 
that’s not a good model.  
* Save your trained neural network with save_model_hdf5. Also save your data sets you used 
for training, testing and validation. 

***

# Some hints 
* Data preprocessing is easier here; no feature engineering is needed. 
* You may be able to reuse parts of the exercises we used in our examples during lectures. 
* All in- and output values need to be floating numbers (or integers in exceptions) in the range of 
[0,1]. 
* Please note that a neural network expects a R matrix or vector, not data frames. Transform your 
data (e.g. a data frame) into a matrix with data.matrix if needed.  
* There are some models which show an accuracy higher than 90% (!) for training (and test) data – 
after learning more than 1000 epochs. 

***

# Important notes
* Single-label, Multiclass classification problem on page 73 in [Deep Learning with R](https://www.manning.com/books/deep-learning-with-r)
* Spaces must be removed in between '```{r}' and '```', else an error with '<!-- rnb-source-end -->' will be produced
* K-Fold Validation on page 83ff and 94ff in [Deep Learning with R](https://www.manning.com/books/deep-learning-with-r)
* Page 110, use Last-Layer activation softmax and loss function categorical_crossentropy
* Convolutional network ausgeschlossen, weil hauptsächlich Pattern recognition/image classification
* Recursive ausgeschlossen, weil hauptsächlich für TimeSeries-Vorhersagen verwendet, oder für Vorhersagen
* Feed-Forward, weil Classification-Task

***

## Data import
```{r}
# install.packages("tidymodels")
# install.packages("themis")
library(here)
library(tidyverse)
library(ggplot2)
library(dplyr)
library(tensorflow)
library(tfdatasets)
library(tidymodels)
library(keras)
library(caret)
library(themis)
#LOAD DATA
setwd(getwd())
dataIn = "../Data/Dataset-part-2.csv"
data_in <- read.csv(dataIn,header = TRUE, sep =',')
#View(data_in)
data <- data.frame(data_in)
summary(data)
plot(data$status)
```
##Cleanup
```{r}
# Check for duplicates 
sum(duplicated(data))
# No duplicates

#Remove ID (irrelevant) and FLAG_MOBIL (always 1)
data <- data %>% select(-ID, -FLAG_MOBIL)
cols <- c("CODE_GENDER","FLAG_OWN_CAR","FLAG_OWN_REALTY","NAME_INCOME_TYPE","NAME_EDUCATION_TYPE", "NAME_FAMILY_STATUS", "NAME_HOUSING_TYPE","FLAG_WORK_PHONE","FLAG_PHONE","FLAG_EMAIL", "OCCUPATION_TYPE","status")
cols
data[cols] <- lapply(data[cols],factor)

# Replacing empty values with "Unknown"
levels(data$OCCUPATION_TYPE) <- c(levels(data$OCCUPATION_TYPE), "Unknown")
data$OCCUPATION_TYPE[is.na(data$OCCUPATION_TYPE)] <- "Unknown"

# Replacing C and X in Status
levels(data$status)[levels(data$status)=="C"] <- "6"
#data$status[data$status == "X"] <- 7
levels(data$status)[levels(data$status)=="X"] <- "7"
# #Convert factors into numericals
# data %<>% mutate_if(is.factor, as.numeric)

summary(data)
```

# Preprocessing
```{r Create a recipe for preproc}
set.seed(1)
trainIndex <- initial_split(data, prop = 0.8, strata = status) 
trainingSet <- training(trainIndex)
testSet <- testing(trainIndex)
status_folds <- vfold_cv(trainingSet, v = 10, strata = status)
status_folds
```
```{r}
# Remove outliers (Out of 1.5x Interquartile Range) only on training set
# CNT_CHILDREN
boxplot(trainingSet$CNT_CHILDREN, horizontal=TRUE, main="CNT_CHILDREN")
Q1_Child <- quantile(trainingSet$CNT_CHILDREN, .25)
Q3_Child <- quantile(trainingSet$CNT_CHILDREN, .75)
IQR_Child <- IQR(trainingSet$CNT_CHILDREN)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$CNT_CHILDREN > (Q1_Child - 1.5*IQR_Child) & trainingSet$CNT_CHILDREN < (Q3_Child + 1.5*IQR_Child))
dim(trainingSet)

# AMT_INCOME_TOTAL
boxplot(trainingSet$AMT_INCOME_TOTAL, horizontal=TRUE, main="AMT_INCOME_TOTAL")
Q1_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .25)
Q3_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .75)
IQR_AIT <- IQR(trainingSet$AMT_INCOME_TOTAL)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$AMT_INCOME_TOTAL > (Q1_AIT - 1.5*IQR_AIT) & trainingSet$AMT_INCOME_TOTAL < (Q3_AIT + 1.5*IQR_AIT))
dim(trainingSet)
```

```{r Create a recipe for preproc2}
set.seed(5)
preprocRecipe <-
  recipe(status ~., data = data) %>%
  step_dummy(all_nominal(), -status,  one_hot = TRUE) %>%
  step_range(all_predictors(), -all_nominal(), min = 0, max = 1)%>%
  step_smote(status, over_ratio = 1) %>%
 # step_downsample(status, under_ratio = 1, skip=TRUE) %>%
 # step_smote(status, over_ratio = 1, skip=TRUE) %>%
 # step_smotenc(status, over_ratio = 1) %>%
 # step_adasyn(status, over_ratio = 1) %>%
 # step_nearmiss(status, over_ratio = 1) %>%
   
  step_dummy(status,  one_hot = TRUE)# %>%
```

# In this step the above defined receipt is extracted using the `prep()` function, and then use the `bake()` function to transform a set of data based on that recipe.
```{r Prep and bake the defined recipe}
# retain = TRUE and new_data = NULL ensures that pre-processed trainingSet is returned 
trainingSet_processed <- preprocRecipe %>%
  prep(trainingSet, retain = TRUE) %>%
  bake(new_data = NULL)
testSet_processed <- preprocRecipe %>%
  prep(testSet) %>%
  bake(new_data =testSet)

#summary(trainingSet_processed)
```

## Check data
```{r}

# sum(trainingSet_processed$status_X0 == 1)
# sum(trainingSet_processed$status_X1 == 1)
# sum(trainingSet_processed$status_X2 == 1)
# sum(trainingSet_processed$status_X3 == 1)
# sum(trainingSet_processed$status_X4 == 1)
# sum(trainingSet_processed$status_X5 == 1)
# sum(trainingSet_processed$status_X6 == 1)
# sum(trainingSet_processed$status_X7 == 1)

# Turn data frame into data matrix
matrix_data <- trainingSet_processed %>% select(-tail(names(trainingSet_processed), 8))
matrix_targets <- trainingSet_processed %>% select(tail(names(trainingSet_processed), 8))

matrix_data_test  <- testSet_processed %>% select(-tail(names(testSet_processed), 8))
matrix_targets_test  <- testSet_processed %>% select(tail(names(testSet_processed), 8))

# summarize the class distribution
percentage <- 100-prop.table(table(data$status)) * 100

#class_counts <- table(data$status)
class_counts <- matrix_targets %>%
  summarize_all(funs(sum(. == 1)))
majority_class_count <- max(class_counts)
relative_class_counts <-  majority_class_count /class_counts

cbind(freq=table(data$status), percentage=percentage)


#Subset only 100 entries for testing
#matrix_data <- matrix_data[1:100, ]
#matrix_targets <- matrix_targets[1:100, ]
```
## Build Model
```{r}
#train_data <- matrix_data
train_data <- data.matrix(matrix_data)
test_data <- data.matrix(matrix_data_test)
train_targets <- data.matrix(matrix_targets)
test_targets <- data.matrix(matrix_targets_test)



# Function to build the model
build_model <- function() {
  model <- keras_model_sequential() %>%
    #layer_batch_normalization(axis = -1L, input_shape = dim(train_data)[[2]]) %>%
    layer_dense(units = 128, activation = "relu", input_shape = dim(train_data)[[2]]) %>%
    #layer_dense(units = 1024, activation = "relu") %>%
    layer_dense(units = 2048, activation = "relu") %>%
    layer_dropout(0.3) %>%
    layer_dense(units = 2048, activation = "relu") %>%
    layer_dropout(0.3) %>%
    layer_dense(units = 128, activation = "relu") %>%
    #layer_dropout(0.3) %>%
    layer_dense(units = 8, activation = "softmax") 

  model %>% compile(
    optimizer = optimizer_sgd(learning_rate = 0.02),
    #optimizer = optimizer_adam(),
    loss = "categorical_crossentropy",
    metrics = "categorical_accuracy"
  )

}
```

```{r}
#Yannick
#install.packages("kerasR")
# library(kerasR)
# model <- keras_model_sequential()
# model %>%
#          layer_dense(units = 64, activation = 'relu', dim(train_data)[[2]]) %>%
#          layer_dropout(rate = 0.2) %>%
#          # layer_dense(units = 30, activation = 'relu') %>%
#          # layer_dropout(rate = 0.3) %>%
#          layer_dense(units = 20, activation = 'relu') %>%
#          layer_dropout(rate = 0.2) %>%
#          layer_dense(units = 8, activation = 'softmax')
# summary(model)
# model %>%
#          compile(loss = 'categorical_crossentropy',
#                  optimizer = 'adam',
#                  metrics = 'accuracy')
# history <- model %>%
#          fit(train_data,
#              train_targets,
#              epochs = 1500,
#              batch_size = 1024,
#              validation_split = 0.2,
#              verbose =2,
#              class_weight = list(relative_class_counts))
# plot(history)
# model %>%
#          evaluate(test_data, test_targets)
# pred <- model %>% predict(test_data, batch_size = 32)
# y_pred = round(pred)
# # Confusion matrix
# library(caret)
# confusion_matrix <- caret::confusionMatrix(matrix(pred), matrix(test_targets))
# length(test_targets)
# table(Predicted = round(pred), Actual = test_targets)

```




## K-Fold-Validation
```{r}

k <- 2
indices <- sample(1:nrow(train_data))
folds <- cut(indices, breaks = k, labels = FALSE)

num_epochs <- 1500
all_acc_histories <- NULL
for (i in 1:k) {
  cat("processing fold #", i, "\n")

  val_indices <- which(folds == i, arr.ind = TRUE)
  val_data <- train_data[val_indices,] #test_data#
  val_targets <- train_targets[val_indices,] #test_targets#

  partial_train_data <- train_data[-val_indices,]
  partial_train_targets <- train_targets[-val_indices,]
  model <- build_model()

  # Train the model (in silent mode, verbose=0)
  # Batch size https://stats.stackexchange.com/questions/153531/what-is-batch-size-in-neural-network
  # One epoch = one forward pass and one backward pass of all the training examples
  # Batch size = the number of training examples in one forward/backward pass. The higher the batch size, the more memory space you'll need.
  # Number of iterations = number of passes, each pass using [batch size] number of examples. To be clear, one pass = one forward pass + one backward pass (we do not count the forward pass and backward pass as two different passes).
  # Batch size 32 much faster than 1, also the smaller the batch the less accurate the estimate of the gradient will be.
  history <- model %>% fit(
    partial_train_data, partial_train_targets,
    validation_data = list(val_data, val_targets),
    epochs = num_epochs, batch_size = 8192, verbose = 2#, class_weights = percentage
  )
  acc_history <- history$metrics$val_categorical_accuracy
  all_acc_histories <- rbind(all_acc_histories, acc_history)
  train_history <- history$metrics$categorical_accuracy
  all_train_histories <- rbind(all_train_histories, train_history)
}


#reticulate::py_last_error()
```

#We can then compute the average of the per-epoch ACC scores for all folds:

```{r}
average_acc_history <- data.frame(
  epoch = seq(1:ncol(all_acc_histories)),
  validation_acc = apply(all_acc_histories, 2, mean),
  training_acc = apply(all_acc_histories, 1, mean)
)

head(max(average_acc_history$validation_acc))

library(ggplot2)
ggplot(average_acc_history, aes(x = epoch, y = validation_acc)) + geom_line()

#It may be a bit hard to see the plot due to scaling issues and relatively high variance. Let's use `geom_smooth()` to try to get a clearer picture:
ggplot(average_acc_history, aes(x = epoch, y = validation_acc)) + geom_smooth()

# Evaluate on Testset
eval <- evaluate(model, test_data, test_targets, verbose = 1)
head(eval)

# # Save model and history, please change the name
#  write.csv(average_acc_history, "../Doc/Versuch 17 - 4 Layer - 512,256,32,8 Full Oversampling SGD 2500 Epochs/Try 17.csv", row.names=FALSE)
#  save_model_hdf5(model, "../Doc/Versuch 17 - 4 Layer - 512,256,32,8 Full Oversampling SGD 2500 Epochs/model 17.hfd5", overwrite = TRUE, include_optimizer = TRUE)
# 
# # Save Training, Testing and Validation Data
#  write.csv(train_data, "../Doc/Versuch 17 - 4 Layer - 512,256,32,8 Full Oversampling SGD 2500 Epochs/train_data.csv", row.names=FALSE)
#  write.csv(test_data, "../Doc/Versuch 17 - 4 Layer - 512,256,32,8 Full Oversampling SGD 2500 Epochs/test_data.csv", row.names=FALSE)
#  write.csv(train_targets, "../Doc/Versuch 17 - 4 Layer - 512,256,32,8 Full Oversampling SGD 2500 Epochs/train_targets.csv", row.names=FALSE)
#  write.csv(test_targets, "../Doc/Versuch 17 - 4 Layer - 512,256,32,8 Full Oversampling SGD 2500 Epochs/test_targets.csv", row.names=FALSE)


# Load model
# Use model_history as precaution
# model_history <- load_model_hdf5("../Doc/Versuch 6/model 6.hfd5", custom_objects = NULL, compile = TRUE)

```